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      name:  <unnamed>
       log:  /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/logfiles/Canary_logfile.log
  log type:  text
 opened on:  30 Jun 2022, 15:35:04

. 
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. label var state_fips "State FIPS"

. label var county_fips "County FIPS"

. label var plant_id "Power Plant ID"

. label var idcountyplant "ID for a plant-county pair"

. label var year "Year"

. label var cinityropr "Power plant initial year of operation"

. label var imr "Infant mortality rate (per 1,000 live births)"

. label var lnimr "log(infant mortality rate)"

. label var births_rs "Number of births by county of residence"

. label var ccapacity "Coal-fired electricity generating capacity"

. label var f_coalq "Coal consumption in electricity generation (in 1,000 tons)"

. label var generation "Net electricity generation (million kilowatt-hours)"

. label var cap30mile_hydro "Hydroelectric capacity within 30 miles of county centroid (in 100s of MW)"

. label var scap1940  "Dummy for BELOW median coal generating capacity in 1940"

. label var bcap1940  "Dummy for ABOVE median coal generating capacity in 1940"

. label var laty "Country centroid latitude"

. label var lony "Country centroid longitude"

. label var yprcp "Total precipitation (in millimeters)"

. label var ytav "Average temperature (in degrees Celsius)"

. label var yddb10 "Degree days below 10 degrees Celsius"

. label var ydda29 "Degree days above 29 degrees Celsius"

. label var dist_miles "Distance between power plant and county centroid"

. label var dist0_10 "Distance between power plant and county centroid -- 0-10 miles"

. label var dist10_20 "Distance between power plant and county centroid -- 10-20 miles"

. label var dist20_30 "Distance between power plant and county centroid -- 20-30 miles"

. label var dist30_40 "Distance between power plant and county centroid -- 30-40 miles"

. label var dist40_50 "Distance between power plant and county centroid -- 40-50 miles"

. label var dist50_60 "Distance between power plant and county centroid -- 50-60 miles"

. label var dist60_70 "Distance between power plant and county centroid -- 60-70 miles"

. label var dist70_80 "Distance between power plant and county centroid -- 70-80 miles"

. label var dist80_90 "Distance between power plant and county centroid -- 80-90 miles"

. label var sulf "Sulfates (in 1000s ug/m-3) based on our coal consumption & AP3 model"

. label var pop "Population"

. label var pop1940 "Population in 1940"

. label var lnpop1940 "log(population in 1940)"

. label var popf15_44 "Female population age 15-44"

. label var spopurb "Share of urban population"

. label var emp "Total employment"

. label var emp1940 "Total employment in 1940"

. label var lnemp1940 "log(total employment in 1940)"

. label var mfg "Manufacturing employment"

. label var smfg "Share of manufacturing employment"

. label var mfg1940 "Manufacturing employment in 1940"

. label var lnmfg1940 "log(Manufacturing employment in 1940)"

. label var light "Share of households with electric lighting"

. label var light1940 "Share of households with electric lighting in 1940"

. label var railroads "Railroad mileage within county in 1911"

. label var inst1944  "Predicted interstate highway from 1944 plan"

. label var control "County 30-90 miles from power plants"

. label var treat "County 0-30 miles from a power plant"

. label var post "Power plant operating"

. label var treatpost "Interaction treat x post"

. label var sc40treatpost "Interaction treatpost x BELOW median coal generating capacity in 1940"

. label var bc40treatpost "Interaction treatpost x ABOVE median coal generating capacity in 1940"

. label var ltreatpost "Interaction treatpost x BELOW median household electricity access in 1940"

. label var htreatpost "Interaction treatpost x ABOVE median household electricity access in 1940"

. label var streatpost "Interaction treatpost x SMALL Plant (< 75MW)"

. label var btreatpost "Interaction treatpost x LARGE Plant (≥ 75MW)"

. label var treatdown_post "Interaction treatpost x DOWNWIND (90◦arc from plant centroid)"

. label var treatup_post "Interaction treatpost x UPWIND (270◦arc from plant centroid)"

. label var treat20post "treatpost w/ alternative treat 0-20 miles from a power plant"

. label var sc40treat20post "Interaction treat20post x BELOW median coal generating capacity in 1940"

. label var bc40treat20post "Interaction treat20post x ABOVE median coal generating capacity in 1940"

. label var ltreat20post "Interaction treat20post x BELOW median household electricity access in 1940"

. label var htreat20post "Interaction treat20post x ABOVE median household electricity access in 1940"

. label var treat40post "treatpost w/ alternative treat 0-40 miles from a power plant"

. label var sc40treat40post "Interaction treat40post x BELOW median coal generating capacity in 1940"

. label var bc40treat40post "Interaction treat40post x ABOVE median coal generating capacity in 1940"

. label var ltreat40post "Interaction treat40post x BELOW median household electricity access in 1940"

. label var htreat40post "Interaction treat40post x ABOVE median household electricity access in 1940"

. label var treat60post "treatpost w/ alternative treat 0-60 miles from a power plant"

. label var treat60postsulf "Interation treat60post x sulf"

. label var evtime "Year - Power plant initial year of operation"

. label var evtimet11b "11 years before plant opening"

. label var evtimet10b "10 years before plant opening"

. label var evtimet9b "9 years before plant opening"

. label var evtimet8b "8 years before plant opening"

. label var evtimet7b "7 years before plant opening"

. label var evtimet6b "6 years before plant opening"

. label var evtimet5b "5 years before plant opening"

. label var evtimet4b "4 years before plant opening"

. label var evtimet3b "3 years before plant opening"

. label var evtimet2b "2 years before plant opening"

. label var evtimet1b "1 year before plant opening"

. label var evtimet0 "Year power plant starts operation"

. label var evtimet1a "1 year after plant opening"

. label var evtimet2a "2 years after plant opening"

. label var evtimet3a "3 years after plant opening"

. label var evtimet4a "4 years after plant opening"

. label var evtimet5a "5 years after plant opening"

. label var evtimet6a "5 years after plant opening"

. label var evtimet7a "7 years after plant opening"

. label var sc40evtimet0 "Interaction evtimet0 x BELOW median coal generating capacity in 1940"

. label var sc40evtimet1a "Interaction evtimet1a x BELOW median coal generating capacity in 1940"

. label var sc40evtimet2a "Interaction evtimet2a x BELOW median coal generating capacity in 1940"

. label var sc40evtimet3a "Interaction evtimet3a x BELOW median coal generating capacity in 1940"

. label var sc40evtimet4a "Interaction evtimet4a x BELOW median coal generating capacity in 1940"

. label var sc40evtimet5a "Interaction evtimet5a x BELOW median coal generating capacity in 1940"

. label var sc40evtimet6a "Interaction evtimet6a x BELOW median coal generating capacity in 1940"

. label var sc40evtimet7a "Interaction evtimet7a x BELOW median coal generating capacity in 1940"

. label var bc40evtimet0 "Interaction evtimet0 x ABOVE median coal generating capacity in 1940"

. label var bc40evtimet1a "Interaction evtimet1a x ABOVE median coal generating capacity in 1940"

. label var bc40evtimet2a "Interaction evtimet2a x ABOVE median coal generating capacity in 1940"

. label var bc40evtimet3a "Interaction evtimet3a x ABOVE median coal generating capacity in 1940"

. label var bc40evtimet4a "Interaction evtimet4a x ABOVE median coal generating capacity in 1940"

. label var bc40evtimet5a "Interaction evtimet5a x ABOVE median coal generating capacity in 1940"

. label var bc40evtimet6a "Interaction evtimet6a x ABOVE median coal generating capacity in 1940"

. label var bc40evtimet7a "Interaction evtimet7a x ABOVE median coal generating capacity in 1940"

. label var levtimet0 "Interaction evtimet0 x BELOW median household electricity access in 1940"

. label var levtimet1a "Interaction evtimet1a x BELOW median household electricity access in 1940"

. label var levtimet2a "Interaction evtimet2a x BELOW median household electricity access in 1940"

. label var levtimet3a "Interaction evtimet3a x BELOW median household electricity access in 1940"

. label var levtimet4a "Interaction evtimet4a x BELOW median household electricity access in 1940"

. label var levtimet5a "Interaction evtimet5a x BELOW median household electricity access in 1940"

. label var levtimet6a "Interaction evtimet6a x BELOW median household electricity access in 1940"

. label var levtimet7a "Interaction evtimet7a x BELOW median household electricity access in 1940"

. label var hevtimet0 "Interaction evtimet0 x ABOVE median household electricity access in 1940"

. label var hevtimet1a "Interaction evtimet1a x ABOVE median household electricity access in 1940"

. label var hevtimet2a "Interaction evtimet2a x ABOVE median household electricity access in 1940"

. label var hevtimet3a "Interaction evtimet3a x ABOVE median household electricity access in 1940"

. label var hevtimet4a "Interaction evtimet4a x ABOVE median household electricity access in 1940"

. label var hevtimet5a "Interaction evtimet5a x ABOVE median household electricity access in 1940"

. label var hevtimet6a "Interaction evtimet6a x ABOVE median household electricity access in 1940"

. label var hevtimet7a "Interaction evtimet7a x ABOVE median household electricity access in 1940"

. 
. keep state_fips county_fips plant_id idcountyplant year cinityropr /*
> */ imr lnimr births_rs ccapacity f_coalq generation cap30mile_hydro scap1940 bcap1940 /*
> */ laty lony yprcp ytav yddb10 ydda29 /*
> */ dist_miles dist0_10 dist10_20 dist20_30 dist30_40 /*
> */ dist40_50 dist50_60 dist60_70 dist70_80 dist80_90 /*
> */ sulf pop pop1940 lnpop1940 popf15_44 spopurb /*
> */ emp emp1940 lnemp1940 mfg smfg mfg1940 lnmfg1940 /*
> */ light light1940 railroads inst1944 /*
> */ control treat post treatpost sc40treatpost bc40treatpost /*
> */ ltreatpost htreatpost streatpost btreatpost /*
> */ treatdown_post treatup_post treat20post sc40treat20post /*
> */ bc40treat20post ltreat20post htreat20post /*
> */ treat40post sc40treat40post bc40treat40post /*
> */ ltreat40post htreat40post treat60post treat60postsulf /*
> */ evtime evtimet11b evtimet10b evtimet9b evtimet8b /*
> */ evtimet7b evtimet6b evtimet5b evtimet4b evtimet3b /*
> */ evtimet2b evtimet1b evtimet0 evtimet1a evtimet2a /*
> */ evtimet3a evtimet4a evtimet5a evtimet6a evtimet7a /*
> */ sc40evtimet0 sc40evtimet1a sc40evtimet2a sc40evtimet3a /*
> */ sc40evtimet4a sc40evtimet5a sc40evtimet6a sc40evtimet7a /*
> */ bc40evtimet0 bc40evtimet1a bc40evtimet2a bc40evtimet3a /*
> */ bc40evtimet4a bc40evtimet5a bc40evtimet6a bc40evtimet7a /*
> */ levtimet0 levtimet1a levtimet2a levtimet3a levtimet4a /*
> */ levtimet5a levtimet6a levtimet7a hevtimet0 hevtimet1a /*
> */ hevtimet2a hevtimet3a hevtimet4a hevtimet5a hevtimet6a /*
> */ hevtimet7a 

. 
. order state_fips county_fips plant_id idcountyplant year cinityropr /*
> */ imr lnimr births_rs ccapacity f_coalq generation cap30mile_hydro scap1940 bcap1940 /*
> */ laty lony yprcp ytav yddb10 ydda29 /*
> */ dist_miles dist0_10 dist10_20 dist20_30 dist30_40 /*
> */ dist40_50 dist50_60 dist60_70 dist70_80 dist80_90 /*
> */ sulf pop pop1940 lnpop1940 popf15_44 spopurb /*
> */ emp emp1940 lnemp1940 mfg smfg mfg1940 lnmfg1940 /*
> */ light light1940 railroads inst1944 /*
> */ control treat post treatpost sc40treatpost bc40treatpost /*
> */ ltreatpost htreatpost streatpost btreatpost /*
> */ treatdown_post treatup_post treat20post sc40treat20post /*
> */ bc40treat20post ltreat20post htreat20post /*
> */ treat40post sc40treat40post bc40treat40post /*
> */ ltreat40post htreat40post treat60post treat60postsulf /*
> */ evtime evtimet11b evtimet10b evtimet9b evtimet8b /*
> */ evtimet7b evtimet6b evtimet5b evtimet4b evtimet3b /*
> */ evtimet2b evtimet1b evtimet0 evtimet1a evtimet2a /*
> */ evtimet3a evtimet4a evtimet5a evtimet6a evtimet7a /*
> */ sc40evtimet0 sc40evtimet1a sc40evtimet2a sc40evtimet3a /*
> */ sc40evtimet4a sc40evtimet5a sc40evtimet6a sc40evtimet7a /*
> */ bc40evtimet0 bc40evtimet1a bc40evtimet2a bc40evtimet3a /*
> */ bc40evtimet4a bc40evtimet5a bc40evtimet6a bc40evtimet7a /*
> */ levtimet0 levtimet1a levtimet2a levtimet3a levtimet4a /*
> */ levtimet5a levtimet6a levtimet7a hevtimet0 hevtimet1a /*
> */ hevtimet2a hevtimet3a hevtimet4a hevtimet5a hevtimet6a /*
> */ hevtimet7a  

. 
. compress
  (0 bytes saved)

. save data/eventstudy_treat30miles_90_11_7.dta, replace
file data/eventstudy_treat30miles_90_11_7.dta saved

. 
. 
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. label var state_fips "State FIPS"

. label var county_fips "County FIPS"

. label var year "Year"

. label var imr "Infant mortality rate (per 1,000 live births)"

. label var lnimr "log(infant mortality rate)"

. label var dimr "Infant mortality rate - change 1940-1930"

. label var births_rs "Number of births by county of residence"

. label var deaths_under_1yr "Number of infant deaths by county of residence"

. label var cap30mile "Coal-fired generating capacity within 30 miles of county centroid (100s of MW)"

. label var cap30mile_1962 "Coal-fired capacity within 30 miles of county centroid (100s of MW) in 1962"

. label var dcap30mile62_38 "Coal capacity within 30 miles of county centroid (100s of MW) - change 1962-1938"

. label var coal30mile "Coal consumption within 30 miles of county centroid (100K Tons)"

. label var cap50mile "Coal-fired generating capacity within 50 miles of county centroid (100s of MW)"

. label var cap100mile "Coal-fired generating capacity within 100 miles of county centroid (100s of MW)"

. label var cap30mile_hydro "Hydroelectric capacity within 30 miles of county centroid (100s of MW)"

. label var cap50mile_hydro "Hydroelectric capacity within 50 miles of county centroid (100s of MW)"

. label var scap1940  "Dummy for BELOW median coal generating capacity in 1940"

. label var bcap1940  "Dummy for ABOVE median coal generating capacity in 1940"

. label var b1950cap30mile "Interaction cap30mile x dummy for BEFORE 1950"

. label var a1950cap30mile "Interaction cap30mile x dummy for AFTER 1950"

. label var scap1940cap30mile "Interaction cap30mile x BELOW median coal generating capacity in 1940"

. label var bcap1940cap30mile "Interaction cap30mile x ABOVE median coal generating capacity in 1940"

. label var sc40b50cap30mile "Interaction scap1940cap30mile x dummy for BEFORE 1950"

. label var bc40b50cap30mile "Interaction bcap1940cap30mile x dummy for BEFORE 1950"

. label var sc40a50cap30mile "Interaction scap1940cap30mile x dummy for AFTER 1950"

. label var bc40a50cap30mile "Interaction bcap1940cap30mile x dummy for AFTER 1950"

. label var scap1940cap50mile "Interaction cap50mile x BELOW median coal generating capacity in 1940"

. label var bcap1940cap50mile "Interaction cap50mile x ABOVE median coal generating capacity in 1940"

. label var scap1940cap100mile "Interaction cap100mile x BELOW median coal generating capacity in 1940"

. label var bcap1940cap100mile "Interaction cap100mile x ABOVE median coal generating capacity in 1940"

. label var cap30mileL2wlight "Interaction cap30mile x BELOW median household electricity access in 1940"

. label var cap30mileH2wlight "Interaction cap30mile x ABOVE median household electricity access in 1940"

. label var cap50mileL2wlight "Interaction cap50mile x BELOW median household electricity access in 1940"

. label var cap50mileH2wlight "Interaction cap50mile x ABOVE median household electricity access in 1940"

. label var cap100mileL2wlight "Interaction cap100mile x BELOW median household electricity access in 1940"

. label var cap100mileH2wlight "Interaction cap100mile x ABOVE median household electricity access in 1940"

. label var amdiarrcap30milelightL2w "Interaction cap30mileL2wlight x ABOVE median infant diarrhea deaths in 1930"

. label var cap30mileL2wlightH2wcoalstove  "Interaction cap30mileL2wlight x ABOVE median use of coal cookstoves in 1940"

. label var cap30milecapdop10l "Interaction cap30mile x dummy for plant operating for <10 years"

. label var cap30milecapdop10m "Interaction cap30mile x dummy for plant operating for ≥10 years"

. label var laty "Country centroid latitude"

. label var lony "Country centroid longitude"

. label var yprcp "Total precipitation (in millimeters)"

. label var ytav "Average temperature (in degrees Celsius)"

. label var yddb10 "Degree days below 10 degrees Celsius"

. label var ydda29 "Degree days above 29 degrees Celsius"

. label var lat "Country centroid latitude"

. label var lon "Country centroid longitude"

. label var yprcpm "Total precipitation (in millimeters) - average of t-4 to t"

. label var ytavm "Average temperature (in degrees Celsius) - average of t-4 to t"

. label var yddb10m "Degree days below 10 degrees Celsius - average of t-4 to t"

. label var ydda29m "Degree days above 29 degrees Celsius - average of t-4 to t"

. label var dist30_1960 "Distance between county centroid and power plant of 30MW or larger in 1960"

. label var n0 "No. obs before coal plant openings - n0=25: no plant within county in the sample"

. label var pop "Population"

. label var pop1940 "Population in 1940"

. label var lnpop1940 "log(population in 1940)"

. label var spopurb "Share of urban population"

. label var ppopurb "Percentage of urban population"

. label var dppopurb "Percentage of urban population - change 1940-1930"

. label var swhite "Share of white population"

. label var pwhite "Percentage of white population"

. label var dpwhite "Percentage of white population - change 1940-1930"

. label var hschool "Share of population 25yo+ with a high school degree"

. label var phschool "Percentage of population 25yo+ with a high school degree"

. label var emp "Total employment"

. label var lnemp "log(total employment)"

. label var emp1940 "Total employment in 1940"

. label var lnemp1940 "long(total employment in 1940)"

. label var dlnemp "log(total employment) - change 1940-1930"

. label var mfg "Manufacturing employment"

. label var lnmfg "log(manufacturing employment)"

. label var smfg "Share of manufacturing employment"

. label var pmfg "Percentage of manufacturing employment"

. label var dpmfg "Percentage of manufacturing employment - change 1940-1930"

. label var mfg1940 "Manufacturing employment in 1940"

. label var lnmfg1940 "log(Manufacturing employment in 1940)"

. label var dmfg "Manufacturing employment - change 1940-1930"

. label var mfgwages_bls90 "Manufacturing payroll per worker (1990 USD)"

. label var lnmfgwages_bls90 "log(manufacturing payroll per worker)"

. label var dmfgwages_bls90 "Manufacturing payroll per worker (1990 USD) - change 1940-1930"

. label var retwages_bls90 "Retail payroll per worker (1990 USD)"

. label var lnretwages_bls90 "log(retail payroll per worker)"

. label var dretwages_bls90 "Retail payroll per worker (1990 USD) - change 1940-1930"

. label var mrhouse_bls90 "Median dwelling rent (1990 USD)"

. label var lnmrhouse_bls90 "log(median dwelling rent)"

. label var dlnmrhouse_bls90 "Median dwelling value (1990 USD) - change 1940-1930"

. label var mvhouse_bls90 "Median dwelling value (1990 USD)"

. label var lnmvhouse_bls90 "log(median dwelling value)"

. label var dlnmvhouse_bls90 "Median dwelling value (1990 USD) - change 1940-1930"

. label var N_mrhouse "Number of obs with information on median dwelling rent"

. label var light "Share of households with electric lighting"

. label var light1940 "Share of households with electric lighting in 1940"

. label var railroads "Railroad mileage within county in 1911 (Donaldson & Hornbeck 2016)"

. label var inst1944  "Predicted interstate highway from 1944 plan (Michaels 2008)"

. label var farmelec "Percentage of farm households with electricity"

. label var runwat "Percentage of households with running water"

. label var elecgasstove "Percentage of households with modern (electric + gas) stoves"

. 
. 
. keep state_fips county_fips year imr lnimr dimr births_rs deaths_under_1yr /*
> */ cap30mile cap30mile_1962 dcap30mile62_38 coal30mile cap50mile cap100mile /*
> */ cap30mile_hydro cap50mile_hydro scap1940 bcap1940 b1950cap30mile a1950cap30mile /*
> */ scap1940cap30mile bcap1940cap30mile sc40b50cap30mile bc40b50cap30mile /*
> */ sc40a50cap30mile bc40a50cap30mile scap1940cap50mile bcap1940cap50mile /*
> */ scap1940cap100mile bcap1940cap100mile cap30mileL2wlight cap30mileH2wlight /*
> */ cap50mileL2wlight cap50mileH2wlight cap100mileL2wlight cap100mileH2wlight /*
> */ amdiarrcap30milelightL2w cap30mileL2wlightH2wcoalstove /* 
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ laty lony yprcp ytav yddb10 ydda29 /*
> */ lat lon yprcpm ytavm yddb10m ydda29m /*
> */ dist30_1960 n0 pop pop1940 lnpop1940 /*
> */ spopurb ppopurb dppopurb swhite pwhite dpwhite hschool phschool /*
> */ emp lnemp emp1940 lnemp1940 dlnemp mfg lnmfg smfg pmfg dpmfg /*
> */ mfg1940 lnmfg1940 dmfg mfgwages_bls90 lnmfgwages_bls90 /*
> */ dmfgwages_bls90 retwages_bls90 lnretwages_bls90 dretwages_bls90 /*
> */ mrhouse_bls90 lnmrhouse_bls90 dlnmrhouse_bls90 N_mrhouse /*
> */ mvhouse_bls90 lnmvhouse_bls90 dlnmvhouse_bls90 /*
> */ light light1940 railroads inst1944 farmelec runwat elecgasstove

. 
. order state_fips county_fips year imr lnimr dimr births_rs deaths_under_1yr /*
> */ cap30mile cap30mile_1962 dcap30mile62_38 coal30mile cap50mile cap100mile /*
> */ cap30mile_hydro cap50mile_hydro scap1940 bcap1940 b1950cap30mile a1950cap30mile /*
> */ scap1940cap30mile bcap1940cap30mile sc40b50cap30mile bc40b50cap30mile /*
> */ sc40a50cap30mile bc40a50cap30mile scap1940cap50mile bcap1940cap50mile /*
> */ scap1940cap100mile bcap1940cap100mile cap30mileL2wlight cap30mileH2wlight /*
> */ cap50mileL2wlight cap50mileH2wlight cap100mileL2wlight cap100mileH2wlight /*
> */ amdiarrcap30milelightL2w cap30mileL2wlightH2wcoalstove /* 
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ laty lony yprcp ytav yddb10 ydda29 /*
> */ lat lon yprcpm ytavm yddb10m ydda29m /*
> */ dist30_1960 n0 pop pop1940 lnpop1940 /*
> */ spopurb ppopurb dppopurb swhite pwhite dpwhite hschool phschool /*
> */ emp lnemp emp1940 lnemp1940 dlnemp mfg lnmfg smfg pmfg dpmfg /*
> */ mfg1940 lnmfg1940 dmfg mfgwages_bls90 lnmfgwages_bls90 /*
> */ dmfgwages_bls90 retwages_bls90 lnretwages_bls90 dretwages_bls90 /*
> */ mrhouse_bls90 lnmrhouse_bls90 dlnmrhouse_bls90 N_mrhouse /*
> */ mvhouse_bls90 lnmvhouse_bls90 dlnmvhouse_bls90 /*
> */ light light1940 railroads inst1944 farmelec runwat elecgasstove

. 
. keep if dist30_1960<=90
(0 observations deleted)

. 
. compress
  (0 bytes saved)

. save data/imr_final_balanced.dta, replace
file data/imr_final_balanced.dta saved

. 
. 
. 
. ********************************************************************************
. ********************************************************************************
. ***FIGURE 1
. ********************************************************************************
. ********************************************************************************
. 
. ****************************************
. ***PANEL A
. ****************************************
. clear all

. use data/HSUS_Electricity2.dta, clear

. 
. keep if (year>=1938 & year<=1962)
(56 observations deleted)

. 
. sort year 

. gen nkilowatts = kilwatts/1000

. gen nffkw = ffkw/1000

. gen ncoaltons = coaltons/1000

. label var nkilowatts "Kilowatt Hours"

. label var nffkw "Fossil Fuel Kilowatt Hours"

. label var ncoaltons "Tons of Coal"

. 
. twoway (line nkilowatt year, sort yaxis(1) lcolor(black) lpattern(solid)) /*
> */ (line nffkw year, sort yaxis(1) lcolor(black) lpattern(dash)) /*
> */ (line ncoaltons year, sort yaxis(2) lcolor(black) lpattern(shortdash)), /*
> */ ytitle("Billions KWH", axis(1)) ylabel(0(200)1000, axis(1)) /*
> */ ytitle("Millions of Short Tons", axis(2)) /*
> */ xtitle("Year") /*
> */ saving(graphs/Fig_1a.gph, replace)
(file graphs/Fig_1a.gph saved)

. graph export graphs/Fig_1a.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/Fig_1a.pdf written in PDF format)

. 
. ****************************************
. ***PANEL B
. ****************************************
. clear all

. use data/coalbysector.dta, clear

. 
. keep if (year>=1938 & year<=1962)
(52 observations deleted)

. 
. sort year

. gen nelectric = electricpower/1000

. gen nmanmining = manufactmining/1000

. gen nretail = retail/1000

. gen nvesselrr = vesselrr/1000

. 
. label var nelectric "Electricity"

. label var nmanmining "Industrial"

. label var nretail "Heating"

. label var nvesselrr "Transportation"

. 
. twoway (line nelectric year, sort lcolor(black) lpattern(solid)) /*
> */ (line nmanmining year, sort lcolor(black) lpattern(dash_dot)) /*
> */ (line nretail year, sort lcolor(black) lpattern(dash)) /*
> */ (line nvesselrr year, sort lcolor(black) lpattern(shortdash)), /*
> */ ytitle("Millions of Short Tons") xtitle("Year") /*
> */ saving(graphs/Fig_1b.gph, replace)
(file graphs/Fig_1b.gph saved)

. graph export graphs/Fig_1b.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/Fig_1b.pdf written in PDF format)

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***FIGURE 2
. ********************************************************************************
. ********************************************************************************
. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. capture drop np

. bysort treat plant_id: gen np = _n

. tab np if treat==1

         np |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        270        1.02        1.02
          2 |        270        1.02        2.05
          3 |        270        1.02        3.07
          4 |        270        1.02        4.09
          5 |        270        1.02        5.11
          6 |        270        1.02        6.14
          7 |        270        1.02        7.16
          8 |        270        1.02        8.18
          9 |        270        1.02        9.20
         10 |        270        1.02       10.23
         11 |        270        1.02       11.25
         12 |        270        1.02       12.27
         13 |        270        1.02       13.30
         14 |        270        1.02       14.32
         15 |        270        1.02       15.34
         16 |        270        1.02       16.36
         17 |        270        1.02       17.39
         18 |        270        1.02       18.41
         19 |        270        1.02       19.43
         20 |        270        1.02       20.45
         21 |        270        1.02       21.48
         22 |        270        1.02       22.50
         23 |        270        1.02       23.52
         24 |        270        1.02       24.55
         25 |        270        1.02       25.57
         26 |        235        0.89       26.46
         27 |        235        0.89       27.35
         28 |        235        0.89       28.24
         29 |        235        0.89       29.13
         30 |        235        0.89       30.02
         31 |        235        0.89       30.91
         32 |        235        0.89       31.80
         33 |        235        0.89       32.69
         34 |        235        0.89       33.58
         35 |        235        0.89       34.47
         36 |        235        0.89       35.36
         37 |        235        0.89       36.25
         38 |        235        0.89       37.14
         39 |        235        0.89       38.03
         40 |        235        0.89       38.92
         41 |        235        0.89       39.81
         42 |        235        0.89       40.70
         43 |        235        0.89       41.59
         44 |        235        0.89       42.48
         45 |        235        0.89       43.37
         46 |        235        0.89       44.26
         47 |        235        0.89       45.15
         48 |        235        0.89       46.04
         49 |        235        0.89       46.93
         50 |        235        0.89       47.82
         51 |        188        0.71       48.53
         52 |        188        0.71       49.25
         53 |        188        0.71       49.96
         54 |        188        0.71       50.67
         55 |        188        0.71       51.38
         56 |        188        0.71       52.09
         57 |        188        0.71       52.81
         58 |        188        0.71       53.52
         59 |        188        0.71       54.23
         60 |        188        0.71       54.94
         61 |        188        0.71       55.66
         62 |        188        0.71       56.37
         63 |        188        0.71       57.08
         64 |        188        0.71       57.79
         65 |        188        0.71       58.50
         66 |        188        0.71       59.22
         67 |        188        0.71       59.93
         68 |        188        0.71       60.64
         69 |        188        0.71       61.35
         70 |        188        0.71       62.06
         71 |        188        0.71       62.78
         72 |        188        0.71       63.49
         73 |        188        0.71       64.20
         74 |        188        0.71       64.91
         75 |        188        0.71       65.63
         76 |        145        0.55       66.17
         77 |        145        0.55       66.72
         78 |        145        0.55       67.27
         79 |        145        0.55       67.82
         80 |        145        0.55       68.37
         81 |        145        0.55       68.92
         82 |        145        0.55       69.47
         83 |        145        0.55       70.02
         84 |        145        0.55       70.57
         85 |        145        0.55       71.12
         86 |        145        0.55       71.67
         87 |        145        0.55       72.22
         88 |        145        0.55       72.77
         89 |        145        0.55       73.31
         90 |        145        0.55       73.86
         91 |        145        0.55       74.41
         92 |        145        0.55       74.96
         93 |        145        0.55       75.51
         94 |        145        0.55       76.06
         95 |        145        0.55       76.61
         96 |        145        0.55       77.16
         97 |        145        0.55       77.71
         98 |        145        0.55       78.26
         99 |        145        0.55       78.81
        100 |        145        0.55       79.36
        101 |        100        0.38       79.73
        102 |        100        0.38       80.11
        103 |        100        0.38       80.49
        104 |        100        0.38       80.87
        105 |        100        0.38       81.25
        106 |        100        0.38       81.63
        107 |        100        0.38       82.01
        108 |        100        0.38       82.39
        109 |        100        0.38       82.77
        110 |        100        0.38       83.14
        111 |        100        0.38       83.52
        112 |        100        0.38       83.90
        113 |        100        0.38       84.28
        114 |        100        0.38       84.66
        115 |        100        0.38       85.04
        116 |        100        0.38       85.42
        117 |        100        0.38       85.80
        118 |        100        0.38       86.17
        119 |        100        0.38       86.55
        120 |        100        0.38       86.93
        121 |        100        0.38       87.31
        122 |        100        0.38       87.69
        123 |        100        0.38       88.07
        124 |        100        0.38       88.45
        125 |        100        0.38       88.83
        126 |         56        0.21       89.04
        127 |         56        0.21       89.25
        128 |         56        0.21       89.46
        129 |         56        0.21       89.67
        130 |         56        0.21       89.89
        131 |         56        0.21       90.10
        132 |         56        0.21       90.31
        133 |         56        0.21       90.52
        134 |         56        0.21       90.73
        135 |         56        0.21       90.95
        136 |         56        0.21       91.16
        137 |         56        0.21       91.37
        138 |         56        0.21       91.58
        139 |         56        0.21       91.80
        140 |         56        0.21       92.01
        141 |         56        0.21       92.22
        142 |         56        0.21       92.43
        143 |         56        0.21       92.64
        144 |         56        0.21       92.86
        145 |         56        0.21       93.07
        146 |         56        0.21       93.28
        147 |         56        0.21       93.49
        148 |         56        0.21       93.70
        149 |         56        0.21       93.92
        150 |         56        0.21       94.13
        151 |         37        0.14       94.27
        152 |         37        0.14       94.41
        153 |         37        0.14       94.55
        154 |         37        0.14       94.69
        155 |         37        0.14       94.83
        156 |         37        0.14       94.97
        157 |         37        0.14       95.11
        158 |         37        0.14       95.25
        159 |         37        0.14       95.39
        160 |         37        0.14       95.53
        161 |         37        0.14       95.67
        162 |         37        0.14       95.81
        163 |         37        0.14       95.95
        164 |         37        0.14       96.09
        165 |         37        0.14       96.23
        166 |         37        0.14       96.37
        167 |         37        0.14       96.51
        168 |         37        0.14       96.65
        169 |         37        0.14       96.79
        170 |         37        0.14       96.93
        171 |         37        0.14       97.07
        172 |         37        0.14       97.21
        173 |         37        0.14       97.35
        174 |         37        0.14       97.49
        175 |         37        0.14       97.63
        176 |         18        0.07       97.70
        177 |         18        0.07       97.77
        178 |         18        0.07       97.84
        179 |         18        0.07       97.91
        180 |         18        0.07       97.97
        181 |         18        0.07       98.04
        182 |         18        0.07       98.11
        183 |         18        0.07       98.18
        184 |         18        0.07       98.25
        185 |         18        0.07       98.31
        186 |         18        0.07       98.38
        187 |         18        0.07       98.45
        188 |         18        0.07       98.52
        189 |         18        0.07       98.59
        190 |         18        0.07       98.66
        191 |         18        0.07       98.72
        192 |         18        0.07       98.79
        193 |         18        0.07       98.86
        194 |         18        0.07       98.93
        195 |         18        0.07       99.00
        196 |         18        0.07       99.06
        197 |         18        0.07       99.13
        198 |         18        0.07       99.20
        199 |         18        0.07       99.27
        200 |         18        0.07       99.34
        201 |          6        0.02       99.36
        202 |          6        0.02       99.38
        203 |          6        0.02       99.41
        204 |          6        0.02       99.43
        205 |          6        0.02       99.45
        206 |          6        0.02       99.47
        207 |          6        0.02       99.50
        208 |          6        0.02       99.52
        209 |          6        0.02       99.54
        210 |          6        0.02       99.56
        211 |          6        0.02       99.59
        212 |          6        0.02       99.61
        213 |          6        0.02       99.63
        214 |          6        0.02       99.66
        215 |          6        0.02       99.68
        216 |          6        0.02       99.70
        217 |          6        0.02       99.72
        218 |          6        0.02       99.75
        219 |          6        0.02       99.77
        220 |          6        0.02       99.79
        221 |          6        0.02       99.81
        222 |          6        0.02       99.84
        223 |          6        0.02       99.86
        224 |          6        0.02       99.88
        225 |          6        0.02       99.91
        226 |          1        0.00       99.91
        227 |          1        0.00       99.91
        228 |          1        0.00       99.92
        229 |          1        0.00       99.92
        230 |          1        0.00       99.92
        231 |          1        0.00       99.93
        232 |          1        0.00       99.93
        233 |          1        0.00       99.94
        234 |          1        0.00       99.94
        235 |          1        0.00       99.94
        236 |          1        0.00       99.95
        237 |          1        0.00       99.95
        238 |          1        0.00       99.95
        239 |          1        0.00       99.96
        240 |          1        0.00       99.96
        241 |          1        0.00       99.97
        242 |          1        0.00       99.97
        243 |          1        0.00       99.97
        244 |          1        0.00       99.98
        245 |          1        0.00       99.98
        246 |          1        0.00       99.98
        247 |          1        0.00       99.99
        248 |          1        0.00       99.99
        249 |          1        0.00      100.00
        250 |          1        0.00      100.00
------------+-----------------------------------
      Total |     26,400      100.00

. *         np |      Freq.     Percent        Cum.
. *------------+-----------------------------------
. *          1 |        270        1.02        1.02
. *number of openings in our sample
. 
. capture drop N

. bysort county_fips treat: gen N = _N

. capture drop np

. bysort treat N plant_id: gen np = _n

. tab np if treat==1 & N==25

         np |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        205        1.58        1.58
          2 |        205        1.58        3.16
          3 |        205        1.58        4.74
          4 |        205        1.58        6.32
          5 |        205        1.58        7.90
          6 |        205        1.58        9.48
          7 |        205        1.58       11.06
          8 |        205        1.58       12.64
          9 |        205        1.58       14.22
         10 |        205        1.58       15.80
         11 |        205        1.58       17.38
         12 |        205        1.58       18.96
         13 |        205        1.58       20.54
         14 |        205        1.58       22.12
         15 |        205        1.58       23.70
         16 |        205        1.58       25.28
         17 |        205        1.58       26.86
         18 |        205        1.58       28.44
         19 |        205        1.58       30.02
         20 |        205        1.58       31.60
         21 |        205        1.58       33.18
         22 |        205        1.58       34.76
         23 |        205        1.58       36.34
         24 |        205        1.58       37.92
         25 |        205        1.58       39.50
         26 |        143        1.10       40.60
         27 |        143        1.10       41.70
         28 |        143        1.10       42.81
         29 |        143        1.10       43.91
         30 |        143        1.10       45.01
         31 |        143        1.10       46.11
         32 |        143        1.10       47.21
         33 |        143        1.10       48.32
         34 |        143        1.10       49.42
         35 |        143        1.10       50.52
         36 |        143        1.10       51.62
         37 |        143        1.10       52.72
         38 |        143        1.10       53.83
         39 |        143        1.10       54.93
         40 |        143        1.10       56.03
         41 |        143        1.10       57.13
         42 |        143        1.10       58.24
         43 |        143        1.10       59.34
         44 |        143        1.10       60.44
         45 |        143        1.10       61.54
         46 |        143        1.10       62.64
         47 |        143        1.10       63.75
         48 |        143        1.10       64.85
         49 |        143        1.10       65.95
         50 |        143        1.10       67.05
         51 |         88        0.68       67.73
         52 |         88        0.68       68.41
         53 |         88        0.68       69.09
         54 |         88        0.68       69.76
         55 |         88        0.68       70.44
         56 |         88        0.68       71.12
         57 |         88        0.68       71.80
         58 |         88        0.68       72.48
         59 |         88        0.68       73.16
         60 |         88        0.68       73.83
         61 |         88        0.68       74.51
         62 |         88        0.68       75.19
         63 |         88        0.68       75.87
         64 |         88        0.68       76.55
         65 |         88        0.68       77.23
         66 |         88        0.68       77.90
         67 |         88        0.68       78.58
         68 |         88        0.68       79.26
         69 |         88        0.68       79.94
         70 |         88        0.68       80.62
         71 |         88        0.68       81.29
         72 |         88        0.68       81.97
         73 |         88        0.68       82.65
         74 |         88        0.68       83.33
         75 |         88        0.68       84.01
         76 |         54        0.42       84.42
         77 |         54        0.42       84.84
         78 |         54        0.42       85.26
         79 |         54        0.42       85.67
         80 |         54        0.42       86.09
         81 |         54        0.42       86.50
         82 |         54        0.42       86.92
         83 |         54        0.42       87.34
         84 |         54        0.42       87.75
         85 |         54        0.42       88.17
         86 |         54        0.42       88.59
         87 |         54        0.42       89.00
         88 |         54        0.42       89.42
         89 |         54        0.42       89.83
         90 |         54        0.42       90.25
         91 |         54        0.42       90.67
         92 |         54        0.42       91.08
         93 |         54        0.42       91.50
         94 |         54        0.42       91.92
         95 |         54        0.42       92.33
         96 |         54        0.42       92.75
         97 |         54        0.42       93.16
         98 |         54        0.42       93.58
         99 |         54        0.42       94.00
        100 |         54        0.42       94.41
        101 |         25        0.19       94.61
        102 |         25        0.19       94.80
        103 |         25        0.19       94.99
        104 |         25        0.19       95.18
        105 |         25        0.19       95.38
        106 |         25        0.19       95.57
        107 |         25        0.19       95.76
        108 |         25        0.19       95.95
        109 |         25        0.19       96.15
        110 |         25        0.19       96.34
        111 |         25        0.19       96.53
        112 |         25        0.19       96.72
        113 |         25        0.19       96.92
        114 |         25        0.19       97.11
        115 |         25        0.19       97.30
        116 |         25        0.19       97.50
        117 |         25        0.19       97.69
        118 |         25        0.19       97.88
        119 |         25        0.19       98.07
        120 |         25        0.19       98.27
        121 |         25        0.19       98.46
        122 |         25        0.19       98.65
        123 |         25        0.19       98.84
        124 |         25        0.19       99.04
        125 |         25        0.19       99.23
        126 |          4        0.03       99.26
        127 |          4        0.03       99.29
        128 |          4        0.03       99.32
        129 |          4        0.03       99.35
        130 |          4        0.03       99.38
        131 |          4        0.03       99.41
        132 |          4        0.03       99.45
        133 |          4        0.03       99.48
        134 |          4        0.03       99.51
        135 |          4        0.03       99.54
        136 |          4        0.03       99.57
        137 |          4        0.03       99.60
        138 |          4        0.03       99.63
        139 |          4        0.03       99.66
        140 |          4        0.03       99.69
        141 |          4        0.03       99.72
        142 |          4        0.03       99.75
        143 |          4        0.03       99.78
        144 |          4        0.03       99.82
        145 |          4        0.03       99.85
        146 |          4        0.03       99.88
        147 |          4        0.03       99.91
        148 |          4        0.03       99.94
        149 |          4        0.03       99.97
        150 |          4        0.03      100.00
------------+-----------------------------------
      Total |     12,975      100.00

. *         np |      Freq.     Percent        Cum.
. *------------+-----------------------------------
. *          1 |        205        1.58        1.58
. *number of openings in which the county affected
. *is not affected by other openings
. 
. 
. reg sulf dist10_20 dist20_30 dist30_40 dist40_50 dist50_60 dist60_70 dist70_80 dist80_90, cluster(county_fips) 

Linear regression                               Number of obs     =    132,000
                                                F(8, 1968)        =       9.77
                                                Prob > F          =     0.0000
                                                R-squared         =     0.0256
                                                Root MSE          =     .85809

                        (Std. Err. adjusted for 1,969 clusters in county_fips)
------------------------------------------------------------------------------
             |               Robust
        sulf |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   dist10_20 |  -.0427161   .0773299    -0.55   0.581    -.1943731     .108941
   dist20_30 |  -.0971124   .0693735    -1.40   0.162    -.2331656    .0389408
   dist30_40 |  -.3944246   .0812464    -4.85   0.000    -.5537626   -.2350866
   dist40_50 |  -.4190537   .0802346    -5.22   0.000    -.5764075      -.2617
   dist50_60 |  -.4334114   .0796128    -5.44   0.000    -.5895456   -.2772771
   dist60_70 |  -.3933987   .0799154    -4.92   0.000    -.5501265   -.2366709
   dist70_80 |  -.4038557   .0798211    -5.06   0.000    -.5603985   -.2473128
   dist80_90 |  -.4142265   .0797445    -5.19   0.000    -.5706189    -.257834
       _cons |   .9660112   .0776306    12.44   0.000     .8137645    1.118258
------------------------------------------------------------------------------

. parmest, saving(data/sulf_dist.dta, replace)
file data/sulf_dist.dta saved

. 
. 
. use data/sulf_dist.dta, clear

. 
. drop if parm=="_cons"
(1 observation deleted)

. 
. gen dist = substr(parm,-5,2)

. destring dist, replace
dist: all characters numeric; replaced as byte

. replace dist = dist +5
(8 real changes made)

. expand 2 if _n==1
(1 observation created)

. replace dist = 5 if _n==9
(1 real change made)

. replace estimate=0 if dist==5
(1 real change made)

. replace min95=0 if dist==5
(1 real change made)

. replace max95=0 if dist==5
(1 real change made)

. sort dist

. 
. keep dist estimate min95 max95

. order dist estimate min95 max95

. 
. twoway (rcap max95 min95 dist, sort msize(1) lcolor(black) lwidth(vthin) lpattern(shortdash)) /*
> */ (connected estimate dist if dist<=25, sort lcolor(black) lwidth(medium) lpattern(solid) mcolor(black) msize(medsmall
> ) msymbol(circle)) /*
> */ (connected estimate dist if dist>25, sort lcolor(black) lwidth(medium) lpattern(solid) mcolor(black) msize(medsmall)
>  msymbol(circle)), /*
> */ ytitle(Concentration of Sulfates) ylabel(, angle(horizontal)) yscale(titlegap(*-40)) /*
> */ xtitle(Distance to Coal-Fired Power Plant (Miles)) /*
> */ xline(30, lwidth(medthick) lpattern(shortdash) lcolor(red)) xlabel(5 "0-10" 15 "10-20" 25 "20-30" 35 "30-40" 45 "40-
> 50" /*
> */ 55 "50-60" 65 "60-70" 75 "70-80" 85 "80-90", angle(45)) legend(off) /*
> */ saving(graphs/Fig_2.gph, replace)
(file graphs/Fig_2.gph saved)

. graph export graphs/Fig_2.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/Fig_2.pdf written in PDF format)

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***FIGURE 3
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. global Geot1 c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econt1 c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. global Econnlnt1 c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ evtimet11b evtimet10b evtimet9b evtimet8b /*
> */ evtimet7b evtimet6b evtimet4b evtimet3b evtimet2b /*
> */ evtimet1b bc40evtimet0 bc40evtimet1a bc40evtimet2a bc40evtimet3a /*
> */ bc40evtimet4a bc40evtimet5a bc40evtimet6a bc40evtimet7a /*
> */ sc40evtimet0 sc40evtimet1a sc40evtimet2a sc40evtimet3a sc40evtimet4a /*
> */ sc40evtimet5a sc40evtimet6a sc40evtimet7a /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  41,   1968) =       9.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6787
                                                  Adj R-squared   =     0.6787
                                                  Within R-sq.    =     0.0368
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7733

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0000414   .0003411    -0.12   0.903    -.0007103    .0006275
                    |
          ccapacity |   .0001874   .0002346     0.80   0.424    -.0002726    .0006474
                    |
      c.year#c.laty |   .0766842   .0118452     6.47   0.000     .0534538    .0999146
                    |
      c.year#c.lony |   .0454118   .0089329     5.08   0.000     .0278928    .0629307
                    |
              yprcp |   .0003954   .0003129     1.26   0.207    -.0002183     .001009
               ytav |   .3050313   .1766223     1.73   0.084     -.041355    .6514176
             ydda29 |  -.0021715   .0026469    -0.82   0.412    -.0073625    .0030194
             yddb10 |   .0002373   .0007426     0.32   0.749    -.0012191    .0016937
                    |
 c.year#c.lnpop1940 |  -.5666176   .1443278    -3.93   0.000    -.8496689   -.2835663
                    |
 c.year#c.lnemp1940 |   .6907872   .1422492     4.86   0.000     .4118122    .9697622
                    |
 c.year#c.lnmfg1940 |  -.0325912   .0234386    -1.39   0.165    -.0785583    .0133759
                    |
 c.year#c.railroads |   -.000204   .0001846    -1.11   0.269     -.000566     .000158
                    |
  c.year#c.inst1944 |   .0230392   .0298751     0.77   0.441    -.0355509    .0816293
                    |
 c.year#c.light1940 |  -.9404805   .1461001    -6.44   0.000    -1.227008   -.6539533
                    |
    cap30mile_hydro |   .0145869    .054103     0.27   0.787    -.0915183    .1206922
         evtimet11b |  -.2075101    .367199    -0.57   0.572    -.9276497    .5126296
         evtimet10b |   .2318533   .2909899     0.80   0.426    -.3388275    .8025341
          evtimet9b |  -.0964243   .2387818    -0.40   0.686     -.564716    .3718674
          evtimet8b |   -.114527   .2229828    -0.51   0.608    -.5518341    .3227801
          evtimet7b |    .017129   .2068957     0.08   0.934    -.3886288    .4228867
          evtimet6b |   .0824254   .1690953     0.49   0.626    -.2491994    .4140501
          evtimet4b |    .248484   .1563147     1.59   0.112    -.0580757    .5550436
          evtimet3b |   .2543423   .1799331     1.41   0.158    -.0985372    .6072218
          evtimet2b |   .4913432   .1738689     2.83   0.005     .1503568    .8323297
          evtimet1b |   .4386711     .18731     2.34   0.019     .0713244    .8060178
       bc40evtimet0 |   .5602344   .2238522     2.50   0.012     .1212222    .9992466
      bc40evtimet1a |   .8638125   .2565795     3.37   0.001     .3606164    1.367009
      bc40evtimet2a |    .702161   .2709618     2.59   0.010     .1707588    1.233563
      bc40evtimet3a |   .9819447   .3161996     3.11   0.002     .3618235    1.602066
      bc40evtimet4a |   1.171471   .3319079     3.53   0.000     .5205427    1.822399
      bc40evtimet5a |   .9930407   .3712851     2.67   0.008     .2648875    1.721194
      bc40evtimet6a |   1.023282   .4003805     2.56   0.011     .2380682    1.808497
      bc40evtimet7a |   1.518493   .4844337     3.13   0.002     .5684357    2.468549
       sc40evtimet0 |   .1424937   .3758816     0.38   0.705     -.594674    .8796614
      sc40evtimet1a |    .234199   .3846033     0.61   0.543    -.5200734    .9884715
      sc40evtimet2a |  -.4108096   .3834797    -1.07   0.284    -1.162879    .3412594
      sc40evtimet3a |  -.2170933   .3973142    -0.55   0.585     -.996294    .5621075
      sc40evtimet4a |  -.1883743   .4032618    -0.47   0.640    -.9792394    .6024908
      sc40evtimet5a |  -.2607753   .4362227    -0.60   0.550    -1.116282    .5947317
      sc40evtimet6a |  -.0655494   .4408498    -0.15   0.882    -.9301309     .799032
      sc40evtimet7a |  -.0418556   .4839312    -0.09   0.931    -.9909271    .9072159
              _cons |   2334.225   1681.011     1.39   0.165    -962.5238    5630.974
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. parmest, saving(data/eventstudy/parmest_sbc40_treat30miles_90_11_7.dta, replace)
file data/eventstudy/parmest_sbc40_treat30miles_90_11_7.dta saved

. 
. 
. use data/eventstudy/parmest_sbc40_treat30miles_90_11_7.dta, clear

. 
. gen var = substr(parm,1,7)

. gen var_aux = substr(parm,1,10)

. replace var = "bc40evtime" if var=="bc40evt"
variable var was str7 now str10
(8 real changes made)

. replace var = "sc40evtime" if var=="sc40evt"
(8 real changes made)

. gen bef_aft = substr(parm,-1,1)

. 
. keep if var=="evtimet" |var=="bc40evtime" |var=="sc40evtime"
(16 observations deleted)

. 
. gen period = substr(parm,-3,2)

. gen period_aux = substr(period,-1,1) 

. gen period_aux2 = substr(period,-2,1) 

. replace period = period_aux if period_aux2=="t"
(22 real changes made)

. replace period = "0" if period=="et"
(2 real changes made)

. destring period, replace
period: all characters numeric; replaced as byte

. drop period_aux period_aux2

. 
. ren estimate estimatet

. 
. keep var period estimatet min95 max95

. order var period estimatet min95 max95

. 
. replace period = period * (-1) if var=="evtimet"
(10 real changes made)

. drop if period==-11 |period==7
(3 observations deleted)

. 
. expand 2 in 1
(1 observation created)

. replace estimatet = 0 in 24
(1 real change made)

. replace min95 = 0 in 24
(1 real change made)

. replace max95 = 0 in 24
(1 real change made)

. replace period = -5 in 24
(1 real change made)

. 
. sort var period

. 
. twoway (rcap max95 min95 period if var=="evtimet" & period>=-10 & period<=0, sort msize(1) lcolor(black) lwidth(vthin) 
> lpattern(shortdash)) /*
> */ (rcap max95 min95 period if var=="bc40evtime" & period>=1 & period<=6, sort msize(1) lcolor(black) lwidth(vthin) lpa
> ttern(shortdash)) /*
> */ (connected estimatet period if var=="evtimet" & period<=-5, sort lcolor(black) lwidth(medium) lpattern(solid) mcolor
> (black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="evtimet" & period>=-4 & period<=0, sort lcolor(black) lwidth(medium) lpattern(s
> olid) mcolor(black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="bc40evtime" & period>=1, sort lcolor(black) lwidth(medium) lpattern(solid) mcol
> or(black) msize(medsmall) msymbol(circle)), /*
> */ title((b) Above Median Generating Capacity in 1940, size(medlarge)) subtitle(" ", margin(l+0 r+0 b-1 t-1)) /*
> */ ytitle(Infant Mortality Rate Per 1000 Live Births) ylabel(-1(0.5)2,angle(0)) /*
> */ xtitle(Years Relative to Power Plant Opening) /*
> */ xline(-4.5 0.5, lwidth(vthin) lpattern(solid) lcolor(black)) xlabel(-10(1)6) legend(off) /* 
> */ text(-0.3 -3.5 "Construction", place(e) box just(center)) /* 
> */ saving(graphs/eventstudy_treat30miles_90_11_7_bcap1940_wCIrange.gph, replace)
(note: file graphs/eventstudy_treat30miles_90_11_7_bcap1940_wCIrange.gph not found)
(file graphs/eventstudy_treat30miles_90_11_7_bcap1940_wCIrange.gph saved)

. 
. twoway (rcap max95 min95 period if var=="evtimet" & period>=-10 & period<=0, sort msize(1) lcolor(black) lwidth(vthin) 
> lpattern(shortdash)) /*
> */ (rcap max95 min95 period if var=="sc40evtime" & period>=1 & period<=6, sort msize(1) lcolor(black) lwidth(vthin) lpa
> ttern(shortdash)) /*
> */ (connected estimatet period if var=="evtimet" & period<=-5, sort lcolor(black) lwidth(medium) lpattern(solid) mcolor
> (black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="evtimet" & period>=-4 & period<=0, sort lcolor(black) lwidth(medium) lpattern(s
> olid) mcolor(black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="sc40evtime" & period>=1, sort lcolor(black) lwidth(medium) lpattern(solid) mcol
> or(black) msize(medsmall) msymbol(circle)), /*
> */ title((a) Below Median Generating Capacity in 1940, size(medlarge)) subtitle(" ", margin(l+0 r+0 b-1 t-1)) /*
> */ ytitle(Infant Mortality Rate Per 1000 Live Births) ylabel(-1(0.5)2,angle(0)) /*
> */ xtitle(Years Relative to Power Plant Opening) /*
> */ xline(-4.5 0.5, lwidth(vthin) lpattern(solid) lcolor(black)) xlabel(-10(1)6) legend(off) /*
> */ text(-0.3 -3.5 "Construction", place(e) box just(center)) /* 
> */ saving(graphs/eventstudy_treat30miles_90_11_7_scap1940_wCIrange.gph, replace)
(note: file graphs/eventstudy_treat30miles_90_11_7_scap1940_wCIrange.gph not found)
(file graphs/eventstudy_treat30miles_90_11_7_scap1940_wCIrange.gph saved)

. 
. graph combine graphs/eventstudy_treat30miles_90_11_7_scap1940_wCIrange.gph graphs/eventstudy_treat30miles_90_11_7_bcap1
> 940_wCIrange.gph, /*
> */ ycommon xcommon iscale(1) xsize(10) saving(graphs/Fig_3.gph, replace)
(file graphs/Fig_3.gph saved)

. graph export graphs/Fig_3.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/Fig_3.pdf written in PDF format)

. 
. erase graphs/eventstudy_treat30miles_90_11_7_scap1940_wCIrange.gph

. erase graphs/eventstudy_treat30miles_90_11_7_bcap1940_wCIrange.gph

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***FIGURE 4
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. global Geot1 c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econt1 c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. global Econnlnt1 c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treat60post treat60postsulf /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      20.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6788
                                                  Adj R-squared   =     0.6788
                                                  Within R-sq.    =     0.0371
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7723

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0003947   .0004871    -0.81   0.418    -.0013499    .0005606
                    |
          ccapacity |   .0003371   .0002495     1.35   0.177    -.0001522    .0008265
                    |
      c.year#c.laty |   .0726758    .012008     6.05   0.000     .0491261    .0962254
                    |
      c.year#c.lony |   .0457677   .0088491     5.17   0.000     .0284132    .0631222
                    |
              yprcp |   .0003966   .0003119     1.27   0.204    -.0002151    .0010084
               ytav |   .2926135   .1777656     1.65   0.100    -.0560151    .6412422
             ydda29 |  -.0025092   .0027289    -0.92   0.358     -.007861    .0028425
             yddb10 |   .0001814   .0007464     0.24   0.808    -.0012824    .0016453
                    |
 c.year#c.lnpop1940 |  -.5663585   .1443428    -3.92   0.000    -.8494393   -.2832777
                    |
 c.year#c.lnemp1940 |   .6904714   .1426985     4.84   0.000     .4106155    .9703273
                    |
 c.year#c.lnmfg1940 |  -.0342681   .0234741    -1.46   0.144    -.0803049    .0117687
                    |
 c.year#c.railroads |  -.0002149   .0001765    -1.22   0.223     -.000561    .0001312
                    |
  c.year#c.inst1944 |   .0251909    .029661     0.85   0.396    -.0329794    .0833612
                    |
 c.year#c.light1940 |  -.8975719   .1471992    -6.10   0.000    -1.186255   -.6088892
                    |
    cap30mile_hydro |   .0052294   .0531302     0.10   0.922     -.098968    .1094268
               post |  -.2468526   .1398704    -1.76   0.078    -.5211622     .027457
        treat60post |  -.4984836   .2358447    -2.11   0.035    -.9610152    -.035952
    treat60postsulf |   .4409777   .1070441     4.12   0.000      .231046    .6509094
              _cons |   2692.371   1684.249     1.60   0.110    -610.7266    5995.469
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. *graph on the net effects
. pctile pctsulf = sulf if e(sample)==1 [fw=births_rs], nq(20)

. gen eff = _b[treat60post] + _b[treat60postsulf] *pctsulf
(131,981 missing values generated)

. gen n5 = _n*5

. replace n5 = . if n5>=100
(131,981 real changes made, 131,981 to missing)

. 
. *pctile sulf 5
. test _b[treat60post] + _b[treat60postsulf] *(.06654741) = 0

 ( 1)  treat60post + .0665474*treat60postsulf = 0

       F(  1,  1968) =    4.09
            Prob > F =    0.0432

. *( 1)  treat60post + .0665474*treat60postsulf = 0
. *F(  1,  1968) =    4.09
. *Prob > F =    0.0432
. 
. *pctile sulf 10
. test _b[treat60post] + _b[treat60postsulf] *(.12201186) = 0

 ( 1)  treat60post + .1220119*treat60postsulf = 0

       F(  1,  1968) =    3.78
            Prob > F =    0.0520

. *( 1)  treat60post + .1220119*treat60postsulf = 0
. *F(  1,  1968) =    3.78
. *Prob > F =    0.0520
. 
. *pctile sulf 15
. test _b[treat60post] + _b[treat60postsulf] *(.19098575) = 0

 ( 1)  treat60post + .1909858*treat60postsulf = 0

       F(  1,  1968) =    3.39
            Prob > F =    0.0657

. *( 1)  treat60post + .1909858*treat60postsulf = 0
. *F(  1,  1968) =    3.39
. *Prob > F =    0.0657
. 
. *pctile sulf 20
. test _b[treat60post] + _b[treat60postsulf] *(.26113662) = 0

 ( 1)  treat60post + .2611366*treat60postsulf = 0

       F(  1,  1968) =    3.00
            Prob > F =    0.0833

. *( 1)  treat60post + .2611366*treat60postsulf = 0
. *F(  1,  1968) =    3.00
. *Prob > F =    0.0833
. 
. *pctile sulf 25
. test _b[treat60post] + _b[treat60postsulf] *(.32751432) = 0

 ( 1)  treat60post + .3275143*treat60postsulf = 0

       F(  1,  1968) =    2.64
            Prob > F =    0.1045

. *( 1)  treat60post + .3275143*treat60postsulf = 0
. *F(  1,  1968) =    2.64
. *Prob > F =    0.1045
. 
. *pctile sulf 75
. test _b[treat60post] + _b[treat60postsulf] *(1.7256587) = 0

 ( 1)  treat60post + 1.725659*treat60postsulf = 0

       F(  1,  1968) =    1.70
            Prob > F =    0.1924

. *( 1)  treat60post + 1.725659*treat60postsulf = 0
. *F(  1,  1968) =    1.70
. *Prob > F =    0.1924
. 
. *pctile sulf 80
. test _b[treat60post] + _b[treat60postsulf] *(2.107451) = 0

 ( 1)  treat60post + 2.107451*treat60postsulf = 0

       F(  1,  1968) =    4.00
            Prob > F =    0.0456

. *( 1)  treat60post + 2.107451*treat60postsulf = 0
. *F(  1,  1968) =    4.00
. *Prob > F =    0.0456
. 
. *pctile sulf 85
. test _b[treat60post] + _b[treat60postsulf] *(2.5201075) = 0

 ( 1)  treat60post + 2.520107*treat60postsulf = 0

       F(  1,  1968) =    6.64
            Prob > F =    0.0100

. *( 1)  treat60post + 2.520107*treat60postsulf = 0
. *F(  1,  1968) =    6.64
. *Prob > F =    0.0100
. 
. *pctile sulf 90
. test _b[treat60post] + _b[treat60postsulf] *(3.2171175) = 0

 ( 1)  treat60post + 3.217118*treat60postsulf = 0

       F(  1,  1968) =   10.27
            Prob > F =    0.0014

. *( 1)  treat60post + 3.217118*treat60postsulf = 0
. *F(  1,  1968) =   10.27
. *Prob > F =    0.0014
. 
. *pctile sulf 95
. test _b[treat60post] + _b[treat60postsulf] *(4.0796723) = 0

 ( 1)  treat60post + 4.079672*treat60postsulf = 0

       F(  1,  1968) =   13.01
            Prob > F =    0.0003

. *( 1)  treat60post + 4.079672*treat60postsulf = 0
. *F(  1,  1968) =   13.01
. *Prob > F =    0.0003
. 
. twoway (connected eff n5, sort lcolor(black) lwidth(medthin) lpattern(solid) mcolor(black) msize(medium) msymbol(circle
> _hollow)) /*
> */ (connected eff n5 if n5<=20, sort lcolor(black) lwidth(medthin) lpattern(solid) mcolor(black) msize(medium) msymbol(
> circle)) /*
> */ (connected eff n5 if n5>=80, sort lcolor(black) lwidth(medthin) lpattern(solid) mcolor(black) msize(medium) msymbol(
> circle)), /*
> */ ytitle(Estimated Net Effects of Plant Openings) ylabel(-.4(.2)1.4, angle(360)) /*
> */ yline(0, lwidth(medthick) lpattern(shortdash) lcolor(red)) /*
> */ xtitle(Percentiles of Air Pollution Concentration From Power Plants) xlabel(5(5)95) legend(off) /*
> */ saving(graphs/Fig4.gph, replace)
(file graphs/Fig4.gph saved)

. graph export graphs/Fig4.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/Fig4.pdf written in PDF format)

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.1
. ********************************************************************************
. ********************************************************************************
. *reproduction from Hales (1976), as mentioned in the notes of the figure
. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.2
. ********************************************************************************
. ********************************************************************************
. *schematic graph made in power point
. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.3
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. collapse (sum) births_rs deaths_under_1yr, by(scap1940 year)

. gen imr = (deaths_under_1yr/births_rs)*1000

. 
. twoway (connected imr year if scap1940==1, sort lcolor(black) lwidth(medthin) /*
> */ lpattern(shortdash) mcolor(black) msize(medsmall) msymbol(circle_hollow)) /*
> */ (connected imr year if scap1940==0, sort lcolor(black) lwidth(medthin) /*
> */ lpattern(solid) mcolor(black) msize(medsmall) msymbol(circle)), /*
> */ ytitle(Infant Mortality Rate per 1000 Live Births) ylabel(25(2)49, angle(ninty)) /*
> */ xtitle("")  xlabel(1938(2)1962, angle(forty_five)) /*
> */ legend(order(1 "Below Median" 2 "Above Median") rows(1) size(3)) /*
> */ saving(graphs/AFig_A3.gph, replace)
(note:  named style ninty not found in class anglestyle, default attributes used)
(file graphs/AFig_A3.gph saved)

. graph export graphs/AFig_A3.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/AFig_A3.pdf written in PDF format)

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.4
. ********************************************************************************
. ********************************************************************************
. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. capture drop n

. bysort county_fips: gen n = _n

. keep if n==1
(130,031 observations deleted)

. 
. keep county_fips treat

. save data/sample_counties_DID_30miles_90.dta, replace
file data/sample_counties_DID_30miles_90.dta saved

. *use this dataset as input to create the map in the software ArcGIS
. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.5
. ********************************************************************************
. ********************************************************************************
. 
. ****************************************
. ***PANEL A
. ****************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. *intermediate steps
. sort county_fips year

. bysort county_fips: gen dcap30mile = cap30mile - cap30mile[_n-1]
(2,027 missing values generated)

. replace dcap30mile = 0 if dcap30mile==.
(2,027 real changes made)

. 
. replace dcap30mile = dcap30mile *100
(4,748 real changes made)

. *coal capacity was measured in 100s of MW, now in MW
. 
. sort county_fips year

. bysort county_fips: gen opening = (dcap30mile>0 & cap30mile[_n-1]==0)

. 
. sort county_fips year

. bysort county_fips: gen upgrade = (dcap30mile>0 & cap30mile[_n-1]>0)

. 
. gen dcap30mileop_aux = dcap30mile if opening==1
(50,041 missing values generated)

. sort county_fips year

. bysort county_fips: gen dcap30mileop = sum(dcap30mileop_aux)

. drop dcap30mileop_aux

. replace dcap30mileop = dcap30mileop/1000
(6,603 real changes made)

. *from megawatt (MW) to gigawatt (GW)
. 
. gen dcap30mileup_aux = dcap30mile if upgrade==1
(46,944 missing values generated)

. sort county_fips year

. bysort county_fips: gen dcap30mileup = sum(dcap30mileup_aux)

. drop dcap30mileup_aux

. replace dcap30mileup = dcap30mileup/1000
(11,252 real changes made)

. *from megawatt (MW) to gigawatt (GW)
. 
. collapse (sum) dcap30mileop (sum) dcap30mileup, by(year)

. 
. label var dcap30mileop "Openings" 

. label var dcap30mileup "Upgrades"

. 
. 
. twoway (area dcap30mileup year if year>=1938, sort fcolor(gray) lcolor(gray)) /*
> */ (area dcap30mileop year if year>=1938, sort fcolor(black) lcolor(black)), /*
> */ ytitle(Coal-Fired Generating Capacity (GW)) ylabel(, angle(horizontal)) /*
> */ xtitle("") xlabel(1938(2)1962, angle(forty_five)) /*
> */ legend(rows(1) order(2 "Openings" 1 "Upgrades")) /*
> */ saving(graphs/AFig_A5a.gph, replace) 
(file graphs/AFig_A5a.gph saved)

. graph export graphs/AFig_A5a.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/AFig_A5a.pdf written in PDF format)

. 
. 
. ****************************************
. ***PANEL B
. ****************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. *intermediate steps
. sort county_fips year

. bysort county_fips: gen dcap30mile = cap30mile - cap30mile[_n-1]
(2,027 missing values generated)

. replace dcap30mile = 0 if dcap30mile==.
(2,027 real changes made)

. 
. replace dcap30mile = dcap30mile *100
(4,748 real changes made)

. *coal capacity was measured in 100s of MW, now in MW
. 
. sort county_fips year

. bysort county_fips: gen opening = (dcap30mile>0 & cap30mile[_n-1]==0)

. 
. sort county_fips year

. bysort county_fips: gen upgrade = (dcap30mile>0 & cap30mile[_n-1]>0)

. 
. 
. *histogram - openings
. histogram dcap30mile if opening==1 & dcap30mile >=50, /*
> */ frequency fcolor(black) lcolor(black) ylabel(, angle(0)) xlabel(0(200)1400) /*
> */ ytitle(Number of Openings) xtitle(Coal Capacity at Opening (MW)) /*
> */ saving(graphs/histogram_openings50mwabove_number.gph, replace)
(bin=18, start=50, width=47.222222)
(note: file graphs/histogram_openings50mwabove_number.gph not found)
(file graphs/histogram_openings50mwabove_number.gph saved)

. 
. *histogram - upgrades
. histogram dcap30mile if upgrade==1 & dcap30mile >=50, /*
> */ frequency fcolor(gray) lcolor(gray) ylabel(0(200)800, angle(0)) xlabel(0(200)1400) /*
> */ ytitle(Number of Upgrades) xtitle(Increased Coal Capacity (MW)) /*
> */ saving(graphs/histogram_upgrades50mwabove_number.gph, replace)
(bin=33, start=50, width=40.160611)
(note: file graphs/histogram_upgrades50mwabove_number.gph not found)
(file graphs/histogram_upgrades50mwabove_number.gph saved)

. 
. graph combine /*
> */ graphs/histogram_openings50mwabove_number.gph /*
> */ graphs/histogram_upgrades50mwabove_number.gph, /*
> */ col(1) xcommon saving(graphs/AFig_A5b.gph, replace)
(file graphs/AFig_A5b.gph saved)

. graph export graphs/AFig_A5b.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/AFig_A5b.pdf written in PDF format)

. 
. erase graphs/histogram_openings50mwabove_number.gph

. erase graphs/histogram_upgrades50mwabove_number.gph

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.6
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. keep if year==1962
(48,648 observations deleted)

. 
. replace dcap30mile62_38 = dcap30mile62_38 *100
(928 real changes made)

. *coal capacity was measured in 100s of MW, now in MW
. 
. keep county_fips dcap30mile62_38

. save data/sample_coal_counties.dta, replace
file data/sample_coal_counties.dta saved

. *use this dataset as input to create the map in the software ArcGIS
. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.7
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. global Geot1 c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econt1 c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. global Econnlnt1 c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ evtimet11b evtimet10b evtimet9b evtimet8b /*
> */ evtimet7b evtimet6b evtimet4b evtimet3b evtimet2b /*
> */ evtimet1b evtimet0 evtimet1a evtimet2a evtimet3a /*
> */ evtimet4a evtimet5a evtimet6a evtimet7a /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  33,   1968) =      10.26
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6786
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0363
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7749

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |   .0000256   .0003385     0.08   0.940    -.0006381    .0006894
                    |
          ccapacity |   .0002939   .0002353     1.25   0.212    -.0001676    .0007554
                    |
      c.year#c.laty |   .0759276   .0119313     6.36   0.000     .0525284    .0993269
                    |
      c.year#c.lony |   .0466493   .0089466     5.21   0.000     .0291034    .0641952
                    |
              yprcp |   .0003979    .000312     1.28   0.202     -.000214    .0010099
               ytav |   .2950609   .1765589     1.67   0.095    -.0512012    .6413231
             ydda29 |  -.0021915   .0026692    -0.82   0.412    -.0074262    .0030432
             yddb10 |   .0001919   .0007419     0.26   0.796    -.0012631    .0016469
                    |
 c.year#c.lnpop1940 |  -.5700013   .1459102    -3.91   0.000     -.856156   -.2838466
                    |
 c.year#c.lnemp1940 |   .7016729   .1441567     4.87   0.000     .4189571    .9843888
                    |
 c.year#c.lnmfg1940 |  -.0341366   .0237523    -1.44   0.151    -.0807189    .0124457
                    |
 c.year#c.railroads |   -.000207   .0001851    -1.12   0.263    -.0005701     .000156
                    |
  c.year#c.inst1944 |   .0240774   .0302004     0.80   0.425    -.0351507    .0833056
                    |
 c.year#c.light1940 |  -.9449144   .1474252    -6.41   0.000     -1.23404   -.6557885
                    |
    cap30mile_hydro |   .0097308   .0544036     0.18   0.858    -.0969639    .1164256
         evtimet11b |   -.111568   .3519738    -0.32   0.751    -.8018484    .5787125
         evtimet10b |   .2866467   .2858569     1.00   0.316    -.2739674    .8472607
          evtimet9b |  -.0537503   .2351702    -0.23   0.819    -.5149592    .4074585
          evtimet8b |  -.0805375   .2211792    -0.36   0.716    -.5143076    .3532327
          evtimet7b |    .043107   .2049159     0.21   0.833     -.358768    .4449821
          evtimet6b |   .0963603   .1684397     0.57   0.567    -.2339787    .4266992
          evtimet4b |   .2319477   .1564403     1.48   0.138    -.0748584    .5387537
          evtimet3b |   .2334363   .1798744     1.30   0.195     -.119328    .5862005
          evtimet2b |   .4661013   .1730638     2.69   0.007     .1266937    .8055089
          evtimet1b |   .4054367    .184995     2.19   0.029       .04263    .7682434
           evtimet0 |   .4207778   .2016401     2.09   0.037     .0253273    .8162282
          evtimet1a |   .6739436   .2249975     3.00   0.003     .2326852    1.115202
          evtimet2a |   .4136867    .231363     1.79   0.074    -.0400556     .867429
          evtimet3a |   .6611302   .2687161     2.46   0.014     .1341322    1.188128
          evtimet4a |   .8032862    .282703     2.84   0.005     .2488575    1.357715
          evtimet5a |   .6415882   .3085921     2.08   0.038     .0363867     1.24679
          evtimet6a |    .692909   .3309924     2.09   0.036     .0437766    1.342041
          evtimet7a |   1.051558    .395881     2.66   0.008      .275168    1.827948
              _cons |   2474.649    1688.46     1.47   0.143    -836.7082    5786.006
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. parmest, saving(data/eventstudy/parmest_treat30miles_90_11_7.dta, replace)
file data/eventstudy/parmest_treat30miles_90_11_7.dta saved

. 
. 
. use data/eventstudy/parmest_treat30miles_90_11_7.dta, clear

. 
. gen var = substr(parm,1,7)

. gen bef_aft = substr(parm,-1,1)

. 
. keep if var=="evtimet"
(16 observations deleted)

. 
. gen period = substr(parm,-3,2)

. gen period_aux = substr(period,-1,1) 

. gen period_aux2 = substr(period,-2,1) 

. replace period = period_aux if period_aux2=="t"
(15 real changes made)

. replace period = "0" if period=="et"
(1 real change made)

. destring period, replace
period: all characters numeric; replaced as byte

. drop period_aux period_aux2

. 
. replace period = period * (-1) if bef_aft~="a"
(10 real changes made)

. drop if period==-11 |period==7
(2 observations deleted)

. 
. ren estimate estimatet

. 
. keep var period estimatet min95 max95

. order var period estimatet min95 max95

. 
. expand 2 in 1
(1 observation created)

. replace estimatet = 0 in 17
(1 real change made)

. replace min95 = 0 in 17
(1 real change made)

. replace max95 = 0 in 17
(1 real change made)

. replace period = -5 in 17
(1 real change made)

. 
. sort var period

. 
. twoway (rcap max95 min95 period if var=="evtimet" & period>=-11 & period<=6, sort msize(1) lcolor(black) lwidth(vthin) 
> lpattern(shortdash)) /*
> */ (connected estimatet period if var=="evtimet" & period<=-5, sort lcolor(black) lwidth(medthin) lpattern(solid) mcolo
> r(black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="evtimet" & period>=-4 & period<=0, sort lcolor(black) lwidth(medthin) lpattern(
> solid) mcolor(black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="evtimet" & period>=1, sort lcolor(black) lwidth(medthin) lpattern(solid) mcolor
> (black) msize(medsmall) msymbol(circle)), /*
> */ ytitle(Infant Mortality Rate Per 1000 Live Births) ylabel(,angle(0)) /*
> */ xtitle(Years Relative to Power Plant Opening) /*
> */ xline(-4.5 0.5, lwidth(vthin) lpattern(solid) lcolor(black)) xlabel(-10(1)6) legend(off) /*
> */ text(-0.3 -3.5 "Construction", place(e) box just(center)) /* 
> */ saving(graphs/AFig_A7.gph, replace)
(file graphs/AFig_A7.gph saved)

. graph export graphs/AFig_A7.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/AFig_A7.pdf written in PDF format)

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.8
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. global Geot1 c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econt1 c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. global Econnlnt1 c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ evtimet11b evtimet10b evtimet9b evtimet8b /*
> */ evtimet7b evtimet6b evtimet4b evtimet3b evtimet2b /*
> */ evtimet1b hevtimet0 hevtimet1a hevtimet2a hevtimet3a /*
> */ hevtimet4a hevtimet5a hevtimet6a hevtimet7a /*
> */ levtimet0 levtimet1a levtimet2a levtimet3a levtimet4a /*
> */ levtimet5a levtimet6a levtimet7a /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  41,   1968) =      10.03
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6787
                                                  Adj R-squared   =     0.6787
                                                  Within R-sq.    =     0.0367
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7735

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0000213    .000343    -0.06   0.950     -.000694    .0006513
                    |
          ccapacity |   .0002378   .0002349     1.01   0.312    -.0002229    .0006986
                    |
      c.year#c.laty |   .0728887   .0122394     5.96   0.000     .0488852    .0968922
                    |
      c.year#c.lony |   .0466147    .008881     5.25   0.000     .0291976    .0640319
                    |
              yprcp |   .0003892   .0003124     1.25   0.213    -.0002234    .0010017
               ytav |   .2991662    .176052     1.70   0.089    -.0461017    .6444342
             ydda29 |   -.002064   .0026143    -0.79   0.430    -.0071912    .0030631
             yddb10 |   .0002046   .0007409     0.28   0.782    -.0012484    .0016577
                    |
 c.year#c.lnpop1940 |  -.5717688    .144803    -3.95   0.000    -.8557522   -.2877855
                    |
 c.year#c.lnemp1940 |    .695088   .1427308     4.87   0.000     .4151687    .9750074
                    |
 c.year#c.lnmfg1940 |  -.0347736   .0235425    -1.48   0.140    -.0809444    .0113973
                    |
 c.year#c.railroads |  -.0001696   .0001851    -0.92   0.360    -.0005325    .0001933
                    |
  c.year#c.inst1944 |   .0253046   .0297516     0.85   0.395    -.0330433    .0836526
                    |
 c.year#c.light1940 |  -.9229817   .1484787    -6.22   0.000    -1.214174   -.6317896
                    |
    cap30mile_hydro |   .0196008   .0539811     0.36   0.717    -.0862654     .125467
         evtimet11b |  -.1987093    .368693    -0.54   0.590    -.9217789    .5243604
         evtimet10b |   .2414318   .2930356     0.82   0.410    -.3332608    .8161245
          evtimet9b |  -.0894187   .2395581    -0.37   0.709     -.559233    .3803956
          evtimet8b |  -.1065169    .222991    -0.48   0.633    -.5438401    .3308064
          evtimet7b |   .0230318   .2064329     0.11   0.911    -.3818182    .4278818
          evtimet6b |   .0863069   .1693061     0.51   0.610    -.2457312    .4183449
          evtimet4b |   .2425246   .1562474     1.55   0.121     -.063903    .5489523
          evtimet3b |   .2491876    .180481     1.38   0.168    -.1047664    .6031416
          evtimet2b |   .4857872   .1752402     2.77   0.006     .1421114     .829463
          evtimet1b |   .4333769   .1883849     2.30   0.022     .0639222    .8028317
          hevtimet0 |   .6163545   .2383533     2.59   0.010     .1489031    1.083806
         hevtimet1a |   .9307368   .2808352     3.31   0.001     .3799712    1.481502
         hevtimet2a |   .7573561   .2974114     2.55   0.011     .1740817     1.34063
         hevtimet3a |   .9635345   .3438841     2.80   0.005     .2891193     1.63795
         hevtimet4a |   1.279253   .3620858     3.53   0.000     .5691414    1.989365
         hevtimet5a |   1.058723   .4024026     2.63   0.009     .2695427    1.847903
         hevtimet6a |   1.180885   .4275178     2.76   0.006     .3424503     2.01932
         hevtimet7a |    1.53529   .5136651     2.99   0.003     .5279052    2.542674
          levtimet0 |   .1172816   .3260791     0.36   0.719    -.5222151    .7567783
         levtimet1a |   .2595273    .319634     0.81   0.417    -.3673293     .886384
         levtimet2a |  -.1910539   .3221694    -0.59   0.553    -.8228829    .4407751
         levtimet3a |    .199071   .3513725     0.57   0.571    -.4900303    .8881723
         levtimet4a |  -.0220769   .3764454    -0.06   0.953    -.7603504    .7161966
         levtimet5a |  -.0499811   .3894917    -0.13   0.898    -.8138406    .7138783
         levtimet6a |  -.1848377   .4087335    -0.45   0.651    -.9864336    .6167582
         levtimet7a |   .3350837    .473524     0.71   0.479    -.5935774    1.263745
              _cons |    2847.16   1713.846     1.66   0.097    -513.9843    6208.304
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. parmest, saving(data/eventstudy/parmest_hl_treat30miles_90_11_7.dta, replace)
file data/eventstudy/parmest_hl_treat30miles_90_11_7.dta saved

. 
. 
. use data/eventstudy/parmest_hl_treat30miles_90_11_7.dta, clear

. 
. gen var = substr(parm,1,7)

. gen bef_aft = substr(parm,-1,1)

. 
. keep if var=="evtimet" |var=="hevtime" |var=="levtime"
(16 observations deleted)

. 
. gen period = substr(parm,-3,2)

. gen period_aux = substr(period,-1,1) 

. gen period_aux2 = substr(period,-2,1) 

. replace period = period_aux if period_aux2=="t"
(22 real changes made)

. replace period = "0" if period=="et"
(2 real changes made)

. destring period, replace
period: all characters numeric; replaced as byte

. drop period_aux period_aux2

. 
. ren estimate estimatet

. 
. keep var period estimatet min95 max95

. order var period estimatet min95 max95

. 
. replace period = period * (-1) if var=="evtimet"
(10 real changes made)

. drop if period==-11 |period==7
(3 observations deleted)

. 
. expand 2 in 1
(1 observation created)

. replace estimatet = 0 in 24
(1 real change made)

. replace min95 = 0 in 24
(1 real change made)

. replace max95 = 0 in 24
(1 real change made)

. replace period = -5 in 24
(1 real change made)

. 
. sort var period

. 
. twoway (rcap max95 min95 period if var=="evtimet" & period>=-10 & period<=0, sort msize(1) lcolor(black) lwidth(vthin) 
> lpattern(shortdash)) /*
> */ (rcap max95 min95 period if var=="hevtime" & period>=1 & period<=6, sort msize(1) lcolor(black) lwidth(vthin) lpatte
> rn(shortdash)) /*
> */ (connected estimatet period if var=="evtimet" & period<=-5, sort lcolor(black) lwidth(medium) lpattern(solid) mcolor
> (black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="evtimet" & period>=-4 & period<=0, sort lcolor(black) lwidth(medium) lpattern(s
> olid) mcolor(black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="hevtime" & period>=1, sort lcolor(black) lwidth(medium) lpattern(solid) mcolor(
> black) msize(medsmall) msymbol(circle)), /*
> */ title((b) Above Median % Households w/ Electricity Access in 1940, size(medlarge)) subtitle(" ", margin(l+0 r+0 b-1 
> t-1)) /*
> */ ytitle(Infant Mortality Rate Per 1000 Live Births) ylabel(-1(0.5)2,angle(0)) /*
> */ xtitle(Years Relative to Power Plant Opening) /*
> */ xline(-4.5 0.5, lwidth(vthin) lpattern(solid) lcolor(black)) xlabel(-10(1)6) legend(off) /* 
> */ text(-0.3 -3.5 "Construction", place(e) box just(center)) /* 
> */ saving(graphs/eventstudy_treat30miles_90_11_7_Hlight_wCIrange.gph, replace)
(note: file graphs/eventstudy_treat30miles_90_11_7_Hlight_wCIrange.gph not found)
(file graphs/eventstudy_treat30miles_90_11_7_Hlight_wCIrange.gph saved)

. 
. twoway (rcap max95 min95 period if var=="evtimet" & period>=-10 & period<=0, sort msize(1) lcolor(black) lwidth(vthin) 
> lpattern(shortdash)) /*
> */ (rcap max95 min95 period if var=="levtime" & period>=1 & period<=6, sort msize(1) lcolor(black) lwidth(vthin) lpatte
> rn(shortdash)) /*
> */ (connected estimatet period if var=="evtimet" & period<=-5, sort lcolor(black) lwidth(medium) lpattern(solid) mcolor
> (black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="evtimet" & period>=-4 & period<=0, sort lcolor(black) lwidth(medium) lpattern(s
> olid) mcolor(black) msize(medsmall) msymbol(circle)) /*
> */ (connected estimatet period if var=="levtime" & period>=1, sort lcolor(black) lwidth(medium) lpattern(solid) mcolor(
> black) msize(medsmall) msymbol(circle)), /*
> */ title((a) Below Median % Households w/ Electricity Access in 1940, size(medlarge)) subtitle(" ", margin(l+0 r+0 b-1 
> t-1)) /*
> */ ytitle(Infant Mortality Rate Per 1000 Live Births) ylabel(-1(0.5)2,angle(0)) /*
> */ xtitle(Years Relative to Power Plant Opening) /*
> */ xline(-4.5 0.5, lwidth(vthin) lpattern(solid) lcolor(black)) xlabel(-10(1)6) legend(off) /*
> */ text(-0.3 -3.5 "Construction", place(e) box just(center)) /* 
> */ saving(graphs/eventstudy_treat30miles_90_11_7_Llight_wCIrange.gph, replace)
(note: file graphs/eventstudy_treat30miles_90_11_7_Llight_wCIrange.gph not found)
(file graphs/eventstudy_treat30miles_90_11_7_Llight_wCIrange.gph saved)

. 
. graph combine graphs/eventstudy_treat30miles_90_11_7_Llight_wCIrange.gph graphs/eventstudy_treat30miles_90_11_7_Hlight_
> wCIrange.gph, /*
> */ ycommon xcommon iscale(1) xsize(10) saving(graphs/AFig_A8.gph, replace)
(file graphs/AFig_A8.gph saved)

. graph export graphs/AFig_A8.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/AFig_A8.pdf written in PDF format)

. 
. erase graphs/eventstudy_treat30miles_90_11_7_Llight_wCIrange.gph 

. erase graphs/eventstudy_treat30miles_90_11_7_Hlight_wCIrange.gph

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX FIGURE A.9
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. collapse ccapacity f_coalq [fw=births_rs], by(evtime)

. drop if evtime==-7 | evtime==7
(2 observations deleted)

. 
. replace f_coalq = 0 if f_coalq==.
(10 real changes made)

. replace f_coalq = f_coalq/100
(7 real changes made)

. *coal measured in 100,000 tons
. 
. expand 2 if evtime<0
(10 observations created)

. 
. sort evtime

. 
. twoway (connected ccapacity evtime if evtime<=-1, sort yaxis(1) lcolor(black) lwidth(medthin) lpattern(solid) mcolor(bl
> ack) msize(medsmall) msymbol(square_hollow)) /*
> */ (connected ccapacity evtime if evtime>=0, sort yaxis(1) lcolor(black) lwidth(medthin) lpattern(solid) mcolor(black) 
> msize(medsmall) msymbol(square_hollow)) /*
> */ (connected f_coalq evtime if evtime<=-1, sort yaxis(2) lcolor(black) lwidth(medthin) lpattern(shortdash) mcolor(blac
> k) msize(medsmall) msymbol(triangle_hollow)) /*
> */ (connected f_coalq evtime if evtime>=0, sort yaxis(2) lcolor(black) lwidth(medthin) lpattern(shortdash) mcolor(black
> ) msize(medsmall) msymbol(triangle_hollow)), /*
> */ ytitle("Coal-Fired Generating Capacity (MW)", axis(1)) ylabel(0(50)300, axis(1) angle(ninty)) /*
> */ ytitle("Coal Consumption (100,000 tons)", axis(2)) ylabel(0(1)8, axis(2) angle(ninty)) /*
> */ xtitle(Years Relative to Power Plant Openings) /*
> */ xline(-0.5, lwidth(thin) lpattern(shortdash) lcolor(black)) xlabel(-6(1)6) /*
> */ legend(order(1 "Capacity" 3 "Consumption") rows(1) size(3.5)) /*
> */ saving(graphs/AFig_A9.gph, replace)
(note:  named style ninty not found in class anglestyle, default attributes used)
(note:  named style ninty not found in class anglestyle, default attributes used)
(file graphs/AFig_A9.gph saved)

. graph export graphs/AFig_A9.pdf, replace
(file /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/graphs/AFig_A9.pdf written in PDF format)

. 
. 
. 
. 
. ********************************************************************************
. ********************************************************************************
. ***TABLE 1
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. global Geot1 c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econt1 c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. global Econnlnt1 c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. ****************************************
. ***PANEL A
. ****************************************
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 /*
> */ post treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  10,   1968) =      10.14
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6728
                                                  Adj R-squared   =     0.6728
                                                  Within R-sq.    =     0.0190
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8264

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0006113   .0004382    -1.40   0.163    -.0014706     .000248
                    |
          ccapacity |   .0010059    .000275     3.66   0.000     .0004666    .0015453
                    |
      c.year#c.laty |   .0739603   .0162041     4.56   0.000     .0421813    .1057394
                    |
      c.year#c.lony |   .0619986   .0121171     5.12   0.000     .0382348    .0857624
                    |
              yprcp |   .0003819   .0003267     1.17   0.243    -.0002588    .0010226
               ytav |   .4015306   .2190594     1.83   0.067    -.0280822    .8311435
             ydda29 |  -.0030719   .0028099    -1.09   0.274    -.0085826    .0024389
             yddb10 |   .0006293   .0009124     0.69   0.490    -.0011601    .0024186
               post |  -.6018303   .1386967    -4.34   0.000    -.8738382   -.3298224
          treatpost |   .8773377   .2147354     4.09   0.000     .4562051     1.29847
              _cons |   4651.504   2223.719     2.09   0.037     290.4117    9012.596
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(T1_PA_c1) se bdec(3) sdec(3) rdec(3) excel replace
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 /*
> */ c.year#c.lnmfg1940 /*
> */ post treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  11,   1968) =      10.68
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6730
                                                  Adj R-squared   =     0.6730
                                                  Within R-sq.    =     0.0195
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8249

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0003049   .0004099    -0.74   0.457    -.0011089     .000499
                    |
          ccapacity |   .0008873   .0002678     3.31   0.001     .0003622    .0014125
                    |
      c.year#c.laty |   .0713579   .0151404     4.71   0.000     .0416649    .1010509
                    |
      c.year#c.lony |   .0588605   .0112087     5.25   0.000     .0368783    .0808427
                    |
              yprcp |   .0003911   .0003268     1.20   0.232    -.0002499    .0010321
               ytav |   .3512035   .2035403     1.73   0.085    -.0479737    .7503806
             ydda29 |  -.0028822   .0028087    -1.03   0.305    -.0083905    .0026261
             yddb10 |   .0004439   .0008521     0.52   0.602    -.0012273     .002115
                    |
 c.year#c.lnmfg1940 |   .0126613   .0088984     1.42   0.155    -.0047899    .0301125
                    |
               post |  -.5403296   .1313701    -4.11   0.000    -.7979687   -.2826905
          treatpost |   .7797844   .2147028     3.63   0.000     .3587156    1.200853
              _cons |   4083.448   2166.948     1.88   0.060    -166.3057    8333.201
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(T1_PA_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  17,   1968) =      15.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6785
                                                  Adj R-squared   =     0.6785
                                                  Within R-sq.    =     0.0362
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7751

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0001989   .0003662    -0.54   0.587    -.0009171    .0005193
                    |
          ccapacity |   .0005522   .0002555     2.16   0.031     .0000512    .0010532
                    |
      c.year#c.laty |    .075773   .0119439     6.34   0.000     .0523491     .099197
                    |
      c.year#c.lony |   .0464917   .0089661     5.19   0.000     .0289076    .0640757
                    |
              yprcp |   .0003901   .0003106     1.26   0.209    -.0002191    .0009992
               ytav |   .2914035   .1773787     1.64   0.101    -.0564663    .6392733
             ydda29 |  -.0022367   .0026736    -0.84   0.403    -.0074801    .0030067
             yddb10 |   .0001793   .0007433     0.24   0.809    -.0012784    .0016369
                    |
 c.year#c.lnpop1940 |  -.5737178   .1465213    -3.92   0.000    -.8610709   -.2863646
                    |
 c.year#c.lnemp1940 |   .7057342    .145045     4.87   0.000     .4212763    .9901921
                    |
 c.year#c.lnmfg1940 |  -.0342414   .0237608    -1.44   0.150    -.0808403    .0123575
                    |
 c.year#c.railroads |  -.0002035   .0001848    -1.10   0.271     -.000566     .000159
                    |
  c.year#c.inst1944 |   .0239572    .030214     0.79   0.428    -.0352976     .083212
                    |
 c.year#c.light1940 |  -.9451938    .147773    -6.40   0.000    -1.235002   -.6553858
                    |
    cap30mile_hydro |   .0048784   .0541433     0.09   0.928    -.1013059    .1110626
               post |  -.4449091   .1217639    -3.65   0.000    -.6837089   -.2061094
          treatpost |   .6090359   .1915582     3.18   0.001     .2333576    .9847142
              _cons |   2481.377   1693.956     1.46   0.143    -840.7585    5803.512
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(T1_PA_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL B
. ****************************************
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 /*
> */ post sc40treatpost bc40treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  11,   1968) =      11.78
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6732
                                                  Adj R-squared   =     0.6732
                                                  Within R-sq.    =     0.0203
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8226

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0007035   .0004497    -1.56   0.118    -.0015855    .0001785
                    |
          ccapacity |   .0008044   .0002689     2.99   0.003     .0002771    .0013317
                    |
      c.year#c.laty |   .0739397   .0157567     4.69   0.000     .0430381    .1048412
                    |
      c.year#c.lony |   .0589499      .0119     4.95   0.000     .0356119    .0822879
                    |
              yprcp |   .0003781   .0003276     1.15   0.249    -.0002644    .0010206
               ytav |   .3916771   .2151712     1.82   0.069    -.0303102    .8136645
             ydda29 |  -.0029865   .0027809    -1.07   0.283    -.0084403    .0024673
             yddb10 |   .0006075   .0008973     0.68   0.498    -.0011523    .0023673
               post |  -.6123723   .1394213    -4.39   0.000    -.8858013   -.3389433
      sc40treatpost |  -.6196163    .366151    -1.69   0.091    -1.337701    .0984682
      bc40treatpost |    1.30335    .252208     5.17   0.000     .8087273    1.797973
              _cons |   4158.185   2197.048     1.89   0.059    -150.6003    8466.971
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test bc40treatpost=sc40treatpost

 ( 1)  - sc40treatpost + bc40treatpost = 0

       F(  1,  1968) =   18.46
            Prob > F =    0.0000

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(T1_PB_c1) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 /*
> */ c.year#c.lnmfg1940 /*
> */ post sc40treatpost bc40treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  12,   1968) =      12.21
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6733
                                                  Adj R-squared   =     0.6733
                                                  Within R-sq.    =     0.0205
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8220

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0004906   .0004249    -1.15   0.248    -.0013238    .0003427
                    |
          ccapacity |   .0007448   .0002676     2.78   0.005     .0002201    .0012696
                    |
      c.year#c.laty |   .0722084   .0149219     4.84   0.000      .042944    .1014727
                    |
      c.year#c.lony |   .0571536   .0111801     5.11   0.000     .0352275    .0790797
                    |
              yprcp |   .0003846   .0003278     1.17   0.241    -.0002583    .0010274
               ytav |   .3591074   .2031416     1.77   0.077    -.0392879    .7575027
             ydda29 |  -.0028684   .0027875    -1.03   0.304    -.0083352    .0025984
             yddb10 |   .0004861   .0008511     0.57   0.568     -.001183    .0021553
                    |
 c.year#c.lnmfg1940 |   .0084328   .0090455     0.93   0.351     -.009307    .0261725
                    |
               post |  -.5703954    .133975    -4.26   0.000    -.8331432   -.3076476
      sc40treatpost |  -.5403473   .3540672    -1.53   0.127    -1.234733    .1540387
      bc40treatpost |   1.197328   .2658999     4.50   0.000     .6758529    1.718803
              _cons |    3827.38    2154.81     1.78   0.076    -398.5703     8053.33
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test bc40treatpost=sc40treatpost

 ( 1)  - sc40treatpost + bc40treatpost = 0

       F(  1,  1968) =   15.38
            Prob > F =    0.0001

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(T1_PB_c2) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post sc40treatpost bc40treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      16.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6787
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0366
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7740

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0003213   .0003799    -0.85   0.398    -.0010664    .0004238
                    |
          ccapacity |   .0004751   .0002552     1.86   0.063    -.0000254    .0009756
                    |
      c.year#c.laty |   .0761937   .0118799     6.41   0.000     .0528952    .0994923
                    |
      c.year#c.lony |   .0455851   .0089461     5.10   0.000     .0280403    .0631299
                    |
              yprcp |   .0003871   .0003112     1.24   0.214    -.0002233    .0009975
               ytav |   .2982854   .1773849     1.68   0.093    -.0495965    .6461673
             ydda29 |  -.0022396   .0026642    -0.84   0.401    -.0074645    .0029853
             yddb10 |   .0002131   .0007441     0.29   0.775    -.0012462    .0016724
                    |
 c.year#c.lnpop1940 |  -.5710179   .1453376    -3.93   0.000    -.8560497    -.285986
                    |
 c.year#c.lnemp1940 |   .6976037    .143632     4.86   0.000     .4159169    .9792906
                    |
 c.year#c.lnmfg1940 |  -.0332069   .0235343    -1.41   0.158    -.0793617    .0129478
                    |
 c.year#c.railroads |  -.0002009   .0001843    -1.09   0.276    -.0005623    .0001605
                    |
  c.year#c.inst1944 |   .0232994   .0299765     0.78   0.437    -.0354896    .0820884
                    |
 c.year#c.light1940 |  -.9414366    .146933    -6.41   0.000    -1.229597   -.6532759
                    |
    cap30mile_hydro |   .0088659   .0537267     0.17   0.869    -.0965013    .1142332
               post |  -.4666041   .1242965    -3.75   0.000    -.7103707   -.2228375
      sc40treatpost |  -.1936537   .3189781    -0.61   0.544    -.8192241    .4319167
      bc40treatpost |   .8704382   .2364355     3.68   0.000      .406748    1.334128
              _cons |   2393.649   1687.905     1.42   0.156    -916.6193    5703.917
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test bc40treatpost=sc40treatpost

 ( 1)  - sc40treatpost + bc40treatpost = 0

       F(  1,  1968) =    7.23
            Prob > F =    0.0072

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(T1_PB_c3) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL C
. ****************************************
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 /*
> */ post ltreatpost htreatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  11,   1968) =      13.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6734
                                                  Adj R-squared   =     0.6734
                                                  Within R-sq.    =     0.0208
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8212

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0006597   .0004535    -1.45   0.146     -.001549    .0002297
                    |
          ccapacity |    .000821   .0002704     3.04   0.002     .0002906    .0013514
                    |
      c.year#c.laty |   .0690083   .0157919     4.37   0.000     .0380377    .0999788
                    |
      c.year#c.lony |    .059351   .0115579     5.14   0.000      .036684    .0820179
                    |
              yprcp |    .000369   .0003267     1.13   0.259    -.0002717    .0010096
               ytav |   .3871818   .2150589     1.80   0.072    -.0345852    .8089488
             ydda29 |  -.0028615   .0027457    -1.04   0.297    -.0082463    .0025232
             yddb10 |   .0005751   .0008963     0.64   0.521    -.0011827    .0023329
               post |  -.6078318   .1403404    -4.33   0.000    -.8830633   -.3326004
         ltreatpost |  -.4367613   .3248416    -1.34   0.179    -1.073831    .2003083
         htreatpost |   1.524871   .2681463     5.69   0.000     .9989903    2.050751
              _cons |   4597.272   2137.393     2.15   0.032     405.4806    8789.063
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test htreatpost=ltreatpost

 ( 1)  - ltreatpost + htreatpost = 0

       F(  1,  1968) =   22.95
            Prob > F =    0.0000

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(T1_PC_c1) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 /*
> */ c.year#c.lnmfg1940 /*
> */ post ltreatpost htreatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  12,   1968) =      13.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6734
                                                  Adj R-squared   =     0.6734
                                                  Within R-sq.    =     0.0209
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8207

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0004753   .0004326    -1.10   0.272    -.0013236     .000373
                    |
          ccapacity |   .0007648   .0002706     2.83   0.005     .0002342    .0012955
                    |
      c.year#c.laty |   .0678428   .0150568     4.51   0.000     .0383138    .0973717
                    |
      c.year#c.lony |   .0576974   .0108745     5.31   0.000     .0363707    .0790242
                    |
              yprcp |   .0003754   .0003272     1.15   0.251    -.0002663     .001017
               ytav |    .358566   .2027066     1.77   0.077    -.0389762    .7561081
             ydda29 |  -.0027653   .0027493    -1.01   0.315    -.0081572    .0026265
             yddb10 |   .0004698   .0008499     0.55   0.581     -.001197    .0021365
                    |
 c.year#c.lnmfg1940 |   .0074686   .0091361     0.82   0.414    -.0104489     .025386
                    |
               post |  -.5711063   .1350498    -4.23   0.000     -.835962   -.3062506
         ltreatpost |  -.3962322   .3148068    -1.26   0.208    -1.013622    .2211575
         htreatpost |      1.419   .2924432     4.85   0.000     .8454693    1.992531
              _cons |   4266.238   2110.917     2.02   0.043     126.3697    8406.106
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test htreatpost=ltreatpost

 ( 1)  - ltreatpost + htreatpost = 0

       F(  1,  1968) =   19.00
            Prob > F =    0.0000

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(T1_PC_c2) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post ltreatpost htreatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      16.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6787
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0366
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7741

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0002947   .0003819    -0.77   0.440    -.0010436    .0004542
                    |
          ccapacity |   .0005045   .0002557     1.97   0.049     3.01e-06    .0010061
                    |
      c.year#c.laty |   .0732899    .012142     6.04   0.000     .0494774    .0971024
                    |
      c.year#c.lony |   .0464599   .0089062     5.22   0.000     .0289932    .0639265
                    |
              yprcp |   .0003821   .0003109     1.23   0.219    -.0002277    .0009919
               ytav |   .2935867   .1769993     1.66   0.097     -.053539    .6407124
             ydda29 |  -.0021973   .0026459    -0.83   0.406    -.0073863    .0029918
             yddb10 |   .0001864   .0007426     0.25   0.802    -.0012701    .0016429
                    |
 c.year#c.lnpop1940 |  -.5756784    .145617    -3.95   0.000    -.8612582   -.2900987
                    |
 c.year#c.lnemp1940 |    .701064   .1439289     4.87   0.000     .4187949    .9833331
                    |
 c.year#c.lnmfg1940 |  -.0347501   .0235858    -1.47   0.141    -.0810058    .0115057
                    |
 c.year#c.railroads |  -.0001723   .0001845    -0.93   0.350    -.0005342    .0001895
                    |
  c.year#c.inst1944 |   .0248975   .0298613     0.83   0.405    -.0336656    .0834606
                    |
 c.year#c.light1940 |  -.9268506   .1488133    -6.23   0.000    -1.218699   -.6350023
                    |
    cap30mile_hydro |   .0124342   .0536831     0.23   0.817    -.0928475     .117716
               post |  -.4641853   .1246653    -3.72   0.000    -.7086751   -.2196955
         ltreatpost |   .0179701    .290646     0.06   0.951    -.5520362    .5879763
         htreatpost |   .9355644   .2652811     3.53   0.000      .415303    1.455826
              _cons |   2786.014     1707.8     1.63   0.103    -563.2737    6135.301
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test htreatpost=ltreatpost

 ( 1)  - ltreatpost + htreatpost = 0

       F(  1,  1968) =    5.30
            Prob > F =    0.0214

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(T1_PC_c3) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***BOTTOM ROWS
. ****************************************
. *number of observations
. reghdfe imr /*
> */ post treatpost /*
> */ , /*
> */ absorb(idcountyplant) cluster(county_fips) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =    132,000
Absorbing 1 HDFE group                            F(   2,   1968) =    1992.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3486
                                                  Adj R-squared   =     0.3214
                                                  Within R-sq.    =     0.1504
Number of clusters (county_fips) =      1,969     Root MSE        =    11.0769

                        (Std. Err. adjusted for 1,969 clusters in county_fips)
------------------------------------------------------------------------------
             |               Robust
         imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        post |  -10.21574   .2002884   -51.01   0.000    -10.60854   -9.822944
   treatpost |   .2595592   .3343896     0.78   0.438    -.3962357    .9153542
       _cons |   36.38478    .074924   485.62   0.000     36.23784    36.53172
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 idcountyplant |      5280        5280           0    *|
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. di e(N)
132000

. 
. *number of county-plant pairs
. reghdfe imr /*
> */ post treatpost /*
> */ , /*
> */ absorb(idcountyplant) cluster(idcountyplant) 
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =    132,000
Absorbing 1 HDFE group                            F(   2,   5279) =    5596.38
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3486
                                                  Adj R-squared   =     0.3214
                                                  Within R-sq.    =     0.1504
Number of clusters (idcountyplant) =      5,280   Root MSE        =    11.0769

                      (Std. Err. adjusted for 5,280 clusters in idcountyplant)
------------------------------------------------------------------------------
             |               Robust
         imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        post |  -10.21574   .1077916   -94.77   0.000    -10.42706   -10.00443
   treatpost |   .2595592   .2376039     1.09   0.275    -.2062427    .7253611
       _cons |   36.38478   .0426164   853.77   0.000     36.30123    36.46832
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 idcountyplant |      5280        5280           0    *|
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. di e(N_clust) 
5280

. 
. *number of counties
. reghdfe imr /*
> */ post treatpost /*
> */ , /*
> */ absorb(idcountyplant) cluster(county_fips)
(MWFE estimator converged in 1 iterations)

HDFE Linear regression                            Number of obs   =    132,000
Absorbing 1 HDFE group                            F(   2,   1968) =    1992.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.3486
                                                  Adj R-squared   =     0.3214
                                                  Within R-sq.    =     0.1504
Number of clusters (county_fips) =      1,969     Root MSE        =    11.0769

                        (Std. Err. adjusted for 1,969 clusters in county_fips)
------------------------------------------------------------------------------
             |               Robust
         imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        post |  -10.21574   .2002884   -51.01   0.000    -10.60854   -9.822944
   treatpost |   .2595592   .3343896     0.78   0.438    -.3962357    .9153542
       _cons |   36.38478    .074924   485.62   0.000     36.23784    36.53172
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-------------------------------------------------------+
   Absorbed FE | Categories  - Redundant  = Num. Coefs |
---------------+---------------------------------------|
 idcountyplant |      5280        5280           0    *|
-------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. di e(N_clust) 
1969

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***TABLE 2
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. global Geo c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econ c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. ****************************************
. ***PANEL A
. ****************************************
. reghdfe imr /*
> */ cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   1,   2026) =      51.43
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6388
                                                  Adj R-squared   =     0.6388
                                                  Within R-sq.    =     0.0184
Number of clusters (county_fips) =      2,027     Root MSE        =     6.2432

                        (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------
             |               Robust
         imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   cap30mile |   .2124883   .0296284     7.17   0.000     .1543829    .2705936
       _cons |   29.09277   .1761107   165.20   0.000      28.7474    29.43815
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      2027        2027           0    *|
        year |        25           0          25     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mile) nocons /*
> */ ctitle(T2_PA_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   1,   2026) =      79.16
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6753
                                                  Adj R-squared   =     0.6753
                                                  Within R-sq.    =     0.0131
Number of clusters (county_fips) =      2,027     Root MSE        =     5.9195

                        (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------
             |               Robust
         imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   cap30mile |    .221904   .0249406     8.90   0.000     .1729922    .2708158
       _cons |    29.0368   .1482461   195.87   0.000     28.74607    29.32754
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mile) nocons /*
> */ ctitle(T2_PA_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  13,   2026) =      15.36
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6791
                                                  Adj R-squared   =     0.6791
                                                  Within R-sq.    =     0.0248
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8842

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0620637   .0121531     5.11   0.000     .0382297    .0858976
                   |
     c.year#c.lony |   .0337393   .0080195     4.21   0.000      .018012    .0494666
                   |
             yprcp |   .0001799   .0002722     0.66   0.509     -.000354    .0007138
              ytav |   .2591277   .1579341     1.64   0.101    -.0506025     .568858
            ydda29 |  -.0057437   .0031951    -1.80   0.072    -.0120097    .0005222
            yddb10 |   .0000995   .0006777     0.15   0.883    -.0012296    .0014286
                   |
c.year#c.lnpop1940 |  -.2131122   .1168471    -1.82   0.068    -.4422652    .0160408
                   |
c.year#c.lnemp1940 |   .3551562   .1155706     3.07   0.002     .1285066    .5818059
                   |
c.year#c.lnmfg1940 |  -.1135736   .0179896    -6.31   0.000    -.1488537   -.0782935
                   |
c.year#c.railroads |  -.0001563   .0001758    -0.89   0.374    -.0005011    .0001884
                   |
 c.year#c.inst1944 |  -.0318023   .0253768    -1.25   0.210    -.0815697     .017965
                   |
   cap30mile_hydro |   .0492161     .06418     0.77   0.443    -.0766495    .1750817
         cap30mile |   .1874939   .0268736     6.98   0.000     .1347912    .2401966
             _cons |   592.4891    1584.16     0.37   0.708    -2514.263    3699.242
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mile) nocons /*
> */ ctitle(T2_PA_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL B
. ****************************************
. reghdfe imr /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips)
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   2,   2026) =      38.79
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6398
                                                  Adj R-squared   =     0.6398
                                                  Within R-sq.    =     0.0212
Number of clusters (county_fips) =      2,027     Root MSE        =     6.2345

                             (Std. Err. adjusted for 2,027 clusters in county_fips)
-----------------------------------------------------------------------------------
                  |               Robust
              imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
scap1940cap30mile |   -.146418   .0508265    -2.88   0.004    -.2460956   -.0467404
bcap1940cap30mile |   .2150445   .0272849     7.88   0.000     .1615351     .268554
            _cons |   29.18727    .156642   186.33   0.000     28.88007    29.49446
-----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      2027        2027           0    *|
        year |        25           0          25     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test scap1940cap30mile=bcap1940cap30mile

 ( 1)  scap1940cap30mile - bcap1940cap30mile = 0

       F(  1,  2026) =   44.00
            Prob > F =    0.0000

. local ttest=r(p) 

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T2_PB_c1) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   2,   2026) =      52.60
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6760
                                                  Adj R-squared   =     0.6760
                                                  Within R-sq.    =     0.0153
Number of clusters (county_fips) =      2,027     Root MSE        =     5.9129

                             (Std. Err. adjusted for 2,027 clusters in county_fips)
-----------------------------------------------------------------------------------
                  |               Robust
              imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
scap1940cap30mile |   -.094286    .048521    -1.94   0.052    -.1894424    .0008703
bcap1940cap30mile |   .2288181   .0247147     9.26   0.000     .1803492    .2772871
            _cons |   29.09376    .143814   202.30   0.000     28.81172    29.37579
-----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test scap1940cap30mile=bcap1940cap30mile

 ( 1)  scap1940cap30mile - bcap1940cap30mile = 0

       F(  1,  2026) =   44.20
            Prob > F =    0.0000

. local ttest=r(p) 

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T2_PB_c2) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      15.91
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6795
                                                  Adj R-squared   =     0.6795
                                                  Within R-sq.    =     0.0259
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8808

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0604739   .0121726     4.97   0.000     .0366018    .0843459
                   |
     c.year#c.lony |      .0303   .0080368     3.77   0.000     .0145388    .0460611
                   |
             yprcp |   .0001958   .0002724     0.72   0.472    -.0003384      .00073
              ytav |   .2606794   .1586635     1.64   0.101    -.0504813      .57184
            ydda29 |  -.0056702   .0031928    -1.78   0.076    -.0119317    .0005912
            yddb10 |   .0001614   .0006793     0.24   0.812    -.0011708    .0014936
                   |
c.year#c.lnpop1940 |   -.209495   .1151003    -1.82   0.069    -.4352224    .0162324
                   |
c.year#c.lnemp1940 |   .3430162   .1137293     3.02   0.003     .1199777    .5660548
                   |
c.year#c.lnmfg1940 |  -.1100548   .0179688    -6.12   0.000     -.145294   -.0748156
                   |
c.year#c.railroads |  -.0001606   .0001735    -0.93   0.355    -.0005008    .0001796
                   |
 c.year#c.inst1944 |  -.0300809   .0251455    -1.20   0.232    -.0793945    .0192328
                   |
   cap30mile_hydro |   .1166962   .0634755     1.84   0.066    -.0077877    .2411802
 scap1940cap30mile |  -.0401813   .0575558    -0.70   0.485    -.1530561    .0726935
 bcap1940cap30mile |   .2030099    .027574     7.36   0.000     .1489335    .2570862
             _cons |   239.9315   1582.933     0.15   0.880    -2864.416    3344.279
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test scap1940cap30mile=bcap1940cap30mile

 ( 1)  scap1940cap30mile - bcap1940cap30mile = 0

       F(  1,  2026) =   18.00
            Prob > F =    0.0000

. local ttest=r(p) 

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T2_PB_c3) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL C
. ****************************************
. reghdfe imr /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   2,   2026) =      43.44
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6402
                                                  Adj R-squared   =     0.6402
                                                  Within R-sq.    =     0.0222
Number of clusters (county_fips) =      2,027     Root MSE        =     6.2312

                             (Std. Err. adjusted for 2,027 clusters in county_fips)
-----------------------------------------------------------------------------------
                  |               Robust
              imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
cap30mileL2wlight |   -.145171   .0428358    -3.39   0.001    -.2291779   -.0611642
cap30mileH2wlight |   .2139324   .0259168     8.25   0.000     .1631059    .2647588
            _cons |   29.36043   .1388476   211.46   0.000     29.08813    29.63273
-----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      2027        2027           0    *|
        year |        25           0          25     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test cap30mileL2wlight=cap30mileH2wlight

 ( 1)  cap30mileL2wlight - cap30mileH2wlight = 0

       F(  1,  2026) =   57.04
            Prob > F =    0.0000

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T2_PC_c1) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   2,   2026) =      46.27
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6758
                                                  Adj R-squared   =     0.6758
                                                  Within R-sq.    =     0.0148
Number of clusters (county_fips) =      2,027     Root MSE        =     5.9144

                             (Std. Err. adjusted for 2,027 clusters in county_fips)
-----------------------------------------------------------------------------------
                  |               Robust
              imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------+----------------------------------------------------------------
cap30mileL2wlight |  -.0356753   .0412348    -0.87   0.387    -.1165423    .0451917
cap30mileH2wlight |   .2334034    .024598     9.49   0.000     .1851634    .2816434
            _cons |   29.18628   .1309527   222.88   0.000     28.92947     29.4431
-----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test cap30mileL2wlight=cap30mileH2wlight

 ( 1)  cap30mileL2wlight - cap30mileH2wlight = 0

       F(  1,  2026) =   33.63
            Prob > F =    0.0000

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T2_PC_c2) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      14.97
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6794
                                                  Adj R-squared   =     0.6793
                                                  Within R-sq.    =     0.0254
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8823

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0549471   .0123546     4.45   0.000      .030718    .0791762
                   |
     c.year#c.lony |   .0344987   .0079727     4.33   0.000     .0188632    .0501342
                   |
             yprcp |    .000162   .0002726     0.59   0.552    -.0003727    .0006967
              ytav |   .2379916   .1576689     1.51   0.131    -.0712184    .5472017
            ydda29 |  -.0050501   .0030899    -1.63   0.102    -.0111097    .0010095
            yddb10 |   .0000603   .0006829     0.09   0.930     -.001279    .0013995
                   |
c.year#c.lnpop1940 |  -.2278037   .1168584    -1.95   0.051    -.4569788    .0013714
                   |
c.year#c.lnemp1940 |   .3623914   .1151092     3.15   0.002     .1366467    .5881361
                   |
c.year#c.lnmfg1940 |  -.1110418   .0181987    -6.10   0.000    -.1467318   -.0753517
                   |
c.year#c.railroads |  -.0001023   .0001748    -0.59   0.558     -.000445    .0002404
                   |
 c.year#c.inst1944 |  -.0291038   .0252916    -1.15   0.250     -.078704    .0204965
                   |
   cap30mile_hydro |   .0582221   .0655018     0.89   0.374    -.0702358    .1866799
 cap30mileL2wlight |   .0013991   .0429151     0.03   0.974    -.0827632    .0855613
 cap30mileH2wlight |   .1954993    .029639     6.60   0.000     .1373731    .2536254
             _cons |   1381.551   1592.701     0.87   0.386    -1741.951    4505.053
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. test cap30mileL2wlight=cap30mileH2wlight

 ( 1)  cap30mileL2wlight - cap30mileH2wlight = 0

       F(  1,  2026) =   17.74
            Prob > F =    0.0000

. local ttest=r(p)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T2_PC_c3) se bdec(3) sdec(3) rdec(3) addstat("ttest", `ttest') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***BOTTOM ROWS
. ****************************************
. reghdfe imr /*
> */ cap30mile /*
> */ , absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 2 iterations)

HDFE Linear regression                            Number of obs   =     50,675
Absorbing 2 HDFE groups                           F(   1,   2026) =       0.56
Statistics robust to heteroskedasticity           Prob > F        =     0.4526
                                                  R-squared       =     0.4374
                                                  Adj R-squared   =     0.4136
                                                  Within R-sq.    =     0.0000
Number of clusters (county_fips) =      2,027     Root MSE        =    10.5128

                        (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------
             |               Robust
         imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   cap30mile |   -.028567   .0380288    -0.75   0.453    -.1031466    .0460126
       _cons |   31.93127   .0408614   781.45   0.000     31.85113     32.0114
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      2027        2027           0    *|
        year |        25           0          25     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. *number of observations
. di e(N)
50675

. 
. *number of counties
. di e(N_clust) 
2027

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***TABLE 3
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. global Geo c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econ c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. ****************************************
. ***PANEL A
. ****************************************
. reghdfe imr /*
> */ b1950cap30mile a1950cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   2,   2026) =      20.83
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6399
                                                  Adj R-squared   =     0.6399
                                                  Within R-sq.    =     0.0215
Number of clusters (county_fips) =      2,027     Root MSE        =     6.2334

                          (Std. Err. adjusted for 2,027 clusters in county_fips)
--------------------------------------------------------------------------------
               |               Robust
           imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
b1950cap30mile |  -.0158732   .0627092    -0.25   0.800    -.1388544    .1071081
a1950cap30mile |   .1434028   .0317165     4.52   0.000     .0812025    .2056032
         _cons |   29.69048   .2087738   142.21   0.000     29.28105    30.09991
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      2027        2027           0    *|
        year |        25           0          25     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(b1950cap30mile a1950cap30mile) nocons /*
> */ ctitle(T3_PA_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ b1950cap30mile a1950cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   2,   2026) =      39.47
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6765
                                                  Adj R-squared   =     0.6765
                                                  Within R-sq.    =     0.0169
Number of clusters (county_fips) =      2,027     Root MSE        =     5.9080

                          (Std. Err. adjusted for 2,027 clusters in county_fips)
--------------------------------------------------------------------------------
               |               Robust
           imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
b1950cap30mile |   -.099433   .0461232    -2.16   0.031    -.1898868   -.0089792
a1950cap30mile |   .1338394   .0243731     5.49   0.000     .0860405    .1816384
         _cons |   29.83423   .1554491   191.92   0.000     29.52937    30.13909
--------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(b1950cap30mile a1950cap30mile) nocons /*
> */ ctitle(T3_PA_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ b1950cap30mile a1950cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      12.17
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6801
                                                  Adj R-squared   =     0.6801
                                                  Within R-sq.    =     0.0278
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8753

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0617556   .0120799     5.11   0.000     .0380653    .0854458
                   |
     c.year#c.lony |    .030722   .0079185     3.88   0.000     .0151927    .0462513
                   |
             yprcp |   .0001778   .0002664     0.67   0.505    -.0003447    .0007002
              ytav |   .2326102   .1550843     1.50   0.134    -.0715312    .5367516
            ydda29 |  -.0053648   .0032519    -1.65   0.099    -.0117422    .0010126
            yddb10 |   .0000676   .0006668     0.10   0.919      -.00124    .0013753
                   |
c.year#c.lnpop1940 |  -.2347355   .1164826    -2.02   0.044    -.4631737   -.0062973
                   |
c.year#c.lnemp1940 |   .3601276   .1150881     3.13   0.002     .1344243    .5858309
                   |
c.year#c.lnmfg1940 |  -.1071761   .0178654    -6.00   0.000    -.1422125   -.0721397
                   |
c.year#c.railroads |   -.000112    .000181    -0.62   0.536     -.000467     .000243
                   |
 c.year#c.inst1944 |  -.0337354    .025797    -1.31   0.191    -.0843268     .016856
                   |
   cap30mile_hydro |    .045837   .0605014     0.76   0.449    -.0728146    .1644885
    b1950cap30mile |  -.0875443   .0450488    -1.94   0.052    -.1758912    .0008026
    a1950cap30mile |   .1213138   .0263056     4.61   0.000      .069725    .1729026
             _cons |   376.9794   1590.247     0.24   0.813    -2741.711     3495.67
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(b1950cap30mile a1950cap30mile) nocons /*
> */ ctitle(T3_PA_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL B
. ****************************************
. reghdfe imr /*
> */ sc40b50cap30mile bc40b50cap30mile sc40a50cap30mile bc40a50cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   4,   2026) =      16.17
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6407
                                                  Adj R-squared   =     0.6407
                                                  Within R-sq.    =     0.0235
Number of clusters (county_fips) =      2,027     Root MSE        =     6.2269

                            (Std. Err. adjusted for 2,027 clusters in county_fips)
----------------------------------------------------------------------------------
                 |               Robust
             imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
sc40b50cap30mile |  -.4771333   .1501486    -3.18   0.002     -.771595   -.1826715
bc40b50cap30mile |   .0151793   .0610008     0.25   0.804    -.1044516    .1348103
sc40a50cap30mile |  -.1619372   .0503421    -3.22   0.001    -.2606649   -.0632096
bc40a50cap30mile |    .154508   .0291882     5.29   0.000     .0972659    .2117501
           _cons |   29.70077    .186555   159.21   0.000     29.33491    30.06663
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      2027        2027           0    *|
        year |        25           0          25     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40b50cap30mile bc40b50cap30mile sc40a50cap30mile bc40a50cap30mile) nocons /*
> */ ctitle(T3_PB_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ sc40b50cap30mile bc40b50cap30mile sc40a50cap30mile bc40a50cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   4,   2026) =      25.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6770
                                                  Adj R-squared   =     0.6770
                                                  Within R-sq.    =     0.0183
Number of clusters (county_fips) =      2,027     Root MSE        =     5.9038

                            (Std. Err. adjusted for 2,027 clusters in county_fips)
----------------------------------------------------------------------------------
                 |               Robust
             imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
sc40b50cap30mile |  -.6108348   .1952128    -3.13   0.002    -.9936736    -.227996
bc40b50cap30mile |  -.0585706   .0429839    -1.36   0.173    -.1428678    .0257267
sc40a50cap30mile |  -.1148304   .0500402    -2.29   0.022     -.212966   -.0166949
bc40a50cap30mile |   .1495126   .0238486     6.27   0.000     .1027423    .1962829
           _cons |   29.79776   .1474711   202.06   0.000     29.50855    30.08697
----------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40b50cap30mile bc40b50cap30mile sc40a50cap30mile bc40a50cap30mile) nocons /*
> */ ctitle(T3_PB_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ sc40b50cap30mile bc40b50cap30mile sc40a50cap30mile bc40a50cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  16,   2026) =      12.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6804
                                                  Adj R-squared   =     0.6804
                                                  Within R-sq.    =     0.0286
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8727

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |     .06071   .0121121     5.01   0.000     .0369566    .0844633
                   |
     c.year#c.lony |   .0290847   .0080029     3.63   0.000     .0133899    .0447796
                   |
             yprcp |   .0001971   .0002665     0.74   0.460    -.0003256    .0007198
              ytav |     .23629   .1557208     1.52   0.129    -.0690996    .5416797
            ydda29 |  -.0053542   .0032403    -1.65   0.099    -.0117089    .0010005
            yddb10 |   .0001179   .0006687     0.18   0.860    -.0011934    .0014292
                   |
c.year#c.lnpop1940 |  -.2326654   .1154124    -2.02   0.044    -.4590048   -.0063259
                   |
c.year#c.lnemp1940 |   .3527804   .1140252     3.09   0.002     .1291615    .5763994
                   |
c.year#c.lnmfg1940 |  -.1053966    .017854    -5.90   0.000    -.1404108   -.0703824
                   |
c.year#c.railroads |  -.0001244   .0001791    -0.69   0.487    -.0004756    .0002268
                   |
 c.year#c.inst1944 |  -.0324417    .025612    -1.27   0.205    -.0826702    .0177868
                   |
   cap30mile_hydro |   .0782572   .0585295     1.34   0.181     -.036527    .1930414
  sc40b50cap30mile |  -.7454443   .1903059    -3.92   0.000     -1.11866   -.3722286
  bc40b50cap30mile |   -.053569   .0438631    -1.22   0.222    -.1395904    .0324524
  sc40a50cap30mile |  -.0610467    .058925    -1.04   0.300    -.1766065    .0545131
  bc40a50cap30mile |   .1397793   .0269587     5.18   0.000     .0869097    .1926489
             _cons |   256.7779   1600.659     0.16   0.873    -2882.331    3395.886
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40b50cap30mile bc40b50cap30mile sc40a50cap30mile bc40a50cap30mile) nocons /*
> */ ctitle(T3_PB_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL C
. ****************************************
. reghdfe imr /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   2,   2026) =      41.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6398
                                                  Adj R-squared   =     0.6397
                                                  Within R-sq.    =     0.0211
Number of clusters (county_fips) =      2,027     Root MSE        =     6.2349

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
cap30milecapdop10l |  -.1596003   .0503656    -3.17   0.002    -.2583741   -.0608264
cap30milecapdop10m |   .2175497   .0278291     7.82   0.000     .1629731    .2721263
             _cons |   29.13661   .1619631   179.90   0.000     28.81898    29.45424
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      2027        2027           0    *|
        year |        25           0          25     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T3_PC_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(   2,   2026) =      56.28
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6759
                                                  Adj R-squared   =     0.6759
                                                  Within R-sq.    =     0.0151
Number of clusters (county_fips) =      2,027     Root MSE        =     5.9134

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
cap30milecapdop10l |  -.1006902    .046523    -2.16   0.031    -.1919281   -.0094523
cap30milecapdop10m |   .2315319   .0240562     9.62   0.000     .1843545    .2787094
             _cons |   29.04469   .1406245   206.54   0.000     28.76891    29.32048
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T3_PC_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      17.01
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6798
                                                  Adj R-squared   =     0.6798
                                                  Within R-sq.    =     0.0267
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8784

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0622405   .0121294     5.13   0.000     .0384532    .0860279
                   |
     c.year#c.lony |    .033603   .0079654     4.22   0.000     .0179818    .0492242
                   |
             yprcp |   .0001748   .0002723     0.64   0.521    -.0003592    .0007089
              ytav |   .2643183   .1588591     1.66   0.096    -.0472259    .5758625
            ydda29 |  -.0057389   .0031907    -1.80   0.072    -.0119964    .0005185
            yddb10 |    .000167   .0006813     0.25   0.806    -.0011692    .0015031
                   |
c.year#c.lnpop1940 |  -.2061076   .1143144    -1.80   0.072    -.4302937    .0180786
                   |
c.year#c.lnemp1940 |   .3405576   .1127846     3.02   0.003     .1193718    .5617435
                   |
c.year#c.lnmfg1940 |  -.1124847   .0178139    -6.31   0.000    -.1474201   -.0775493
                   |
c.year#c.railroads |  -.0001797    .000172    -1.04   0.296     -.000517    .0001576
                   |
 c.year#c.inst1944 |  -.0293203   .0249301    -1.18   0.240    -.0782116    .0195709
                   |
   cap30mile_hydro |   .0396028   .0638252     0.62   0.535     -.085567    .1647725
cap30milecapdop10l |   -.122444   .0459268    -2.67   0.008    -.2125126   -.0323754
cap30milecapdop10m |   .2095409   .0274556     7.63   0.000     .1556966    .2633851
             _cons |   686.2048   1580.677     0.43   0.664    -2413.717    3786.126
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T3_PC_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***BOTTOM ROWS
. ****************************************
. reghdfe imr /*
> */ cap30mile /*
> */ , absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 2 iterations)

HDFE Linear regression                            Number of obs   =     50,675
Absorbing 2 HDFE groups                           F(   1,   2026) =       0.56
Statistics robust to heteroskedasticity           Prob > F        =     0.4526
                                                  R-squared       =     0.4374
                                                  Adj R-squared   =     0.4136
                                                  Within R-sq.    =     0.0000
Number of clusters (county_fips) =      2,027     Root MSE        =    10.5128

                        (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------
             |               Robust
         imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   cap30mile |   -.028567   .0380288    -0.75   0.453    -.1031466    .0460126
       _cons |   31.93127   .0408614   781.45   0.000     31.85113     32.0114
------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      2027        2027           0    *|
        year |        25           0          25     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. *number of observations
. di e(N)
50675

. 
. *number of counties
. di e(N_clust) 
2027

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***TABLE 4
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. global Geo c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Geo3 c.year#c.lat c.year#c.lon yprcpm ytavm ydda29m yddb10m

. 
. global Econ c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. reghdfe farmelec /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30mileH2wlight cap30mileL2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 3 iterations)

HDFE Linear regression                            Number of obs   =  4,271,553
Absorbing 2 HDFE groups                           F(  14,   1958) =      62.02
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9303
                                                  Adj R-squared   =     0.9303
                                                  Within R-sq.    =     0.5396
Number of clusters (county_fips) =      1,959     Root MSE        =     7.6597

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
          farmelec |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0803181     .01954    -4.11   0.000    -.1186396   -.0419967
                   |
      c.year#c.lon |   .0243309   .0165886     1.47   0.143    -.0082022    .0568639
                   |
            yprcpm |   .0227753   .0074879     3.04   0.002     .0080902    .0374605
             ytavm |   .5010986   3.488512     0.14   0.886    -6.340489    7.342686
           ydda29m |  -.0516008   .0557014    -0.93   0.354    -.1608411    .0576395
           yddb10m |   .0271284   .0107082     2.53   0.011     .0061276    .0481291
                   |
c.year#c.lnpop1940 |   .7829179   .5815921     1.35   0.178    -.3576867    1.923522
                   |
c.year#c.lnemp1940 |  -.8252615   .6339169    -1.30   0.193    -2.068484    .4179613
                   |
c.year#c.lnmfg1940 |  -.5022928   .1524136    -3.30   0.001    -.8012028   -.2033827
                   |
c.year#c.railroads |  -.0012765   .0014099    -0.91   0.365    -.0040414    .0014885
                   |
 c.year#c.inst1944 |  -.0820858   .1569077    -0.52   0.601    -.3898096    .2256379
                   |
   cap30mile_hydro |   5.140014   1.184727     4.34   0.000     2.816556    7.463473
 cap30mileH2wlight |   .3414615   1.250393     0.27   0.785    -2.110779    2.793702
 cap30mileL2wlight |   1.633103   .6868285     2.38   0.018     .2861116    2.980095
             _cons |   18671.73   4906.418     3.81   0.000     9049.377    28294.08
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         2           0           2     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileH2wlight cap30mileL2wlight) nocons /*
> */ ctitle(T4_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe runwat /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30mileH2wlight cap30mileL2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,328,960
Absorbing 2 HDFE groups                           F(  14,   1958) =      63.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9648
                                                  Adj R-squared   =     0.9648
                                                  Within R-sq.    =     0.5693
Number of clusters (county_fips) =      1,959     Root MSE        =     4.2345

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
            runwat |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0123732   .0092156    -1.34   0.180    -.0304466    .0057002
                   |
      c.year#c.lon |  -.0060531   .0032946    -1.84   0.066    -.0125145    .0004082
                   |
            yprcpm |  -.0056925    .003391    -1.68   0.093    -.0123429    .0009579
             ytavm |  -.0386212   .9406452    -0.04   0.967    -1.883392     1.80615
           ydda29m |   -.044725   .0299523    -1.49   0.136    -.1034667    .0140168
           yddb10m |   .0040581   .0052631     0.77   0.441    -.0062638    .0143801
                   |
c.year#c.lnpop1940 |  -.1907945   .1582312    -1.21   0.228    -.5011138    .1195249
                   |
c.year#c.lnemp1940 |  -.0638199   .1509396    -0.42   0.672     -.359839    .2321992
                   |
c.year#c.lnmfg1940 |  -.1004027   .0198985    -5.05   0.000    -.1394273   -.0613782
                   |
c.year#c.railroads |   .0002255   .0004064     0.55   0.579    -.0005715    .0010225
                   |
 c.year#c.inst1944 |   .0045941   .0330893     0.14   0.890    -.0602999    .0694881
                   |
   cap30mile_hydro |   .6152592   .5965256     1.03   0.302    -.5546328    1.785151
 cap30mileH2wlight |   .0696494   .0749087     0.93   0.353    -.0772597    .2165586
 cap30mileL2wlight |   .4156887   .0858453     4.84   0.000      .247331    .5840465
             _cons |   7438.112   1394.566     5.33   0.000     4703.122     10173.1
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileH2wlight cap30mileL2wlight) nocons /*
> */ ctitle(T4_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe elecgasstove /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30mileH2wlight cap30mileL2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,337,558
Absorbing 2 HDFE groups                           F(  14,   1958) =     166.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9539
                                                  Adj R-squared   =     0.9539
                                                  Within R-sq.    =     0.6882
Number of clusters (county_fips) =      1,959     Root MSE        =     6.0163

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
      elecgasstove |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   -.060193   .0064788    -9.29   0.000    -.0728991    -.047487
                   |
      c.year#c.lon |   .0239892   .0042147     5.69   0.000     .0157234     .032255
                   |
            yprcpm |    -.00214   .0023537    -0.91   0.363    -.0067559     .002476
             ytavm |  -3.178692    .897367    -3.54   0.000    -4.938587   -1.418797
           ydda29m |  -.0338109   .0288844    -1.17   0.242    -.0904582    .0228365
           yddb10m |  -.0189361   .0039914    -4.74   0.000    -.0267639   -.0111083
                   |
c.year#c.lnpop1940 |  -.1316518   .1946303    -0.68   0.499    -.5133561    .2500525
                   |
c.year#c.lnemp1940 |  -.3059872   .1792277    -1.71   0.088    -.6574844      .04551
                   |
c.year#c.lnmfg1940 |  -.2093113   .0335575    -6.24   0.000    -.2751235   -.1434991
                   |
c.year#c.railroads |   .0019811   .0003839     5.16   0.000     .0012282    .0027339
                   |
 c.year#c.inst1944 |  -.1183966    .054854    -2.16   0.031     -.225975   -.0108182
                   |
   cap30mile_hydro |   3.600072    .913165     3.94   0.000     1.809195     5.39095
 cap30mileH2wlight |   -.007115   .0701785    -0.10   0.919    -.1447473    .1305174
 cap30mileL2wlight |   .4345143   .1649419     2.63   0.008     .1110341    .7579946
             _cons |   21465.99   1316.605    16.30   0.000      18883.9    24048.09
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileH2wlight cap30mileL2wlight) nocons /*
> */ ctitle(T4_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mileH2wlight cap30mileL2wlight amdiarrcap30milelightL2w /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  15,   2026) =      14.87
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6795
                                                  Adj R-squared   =     0.6795
                                                  Within R-sq.    =     0.0260
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8807

                                    (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------------
                         |               Robust
                     imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
           c.year#c.laty |   .0564277   .0123331     4.58   0.000     .0322408    .0806147
                         |
           c.year#c.lony |   .0337242    .007915     4.26   0.000     .0182018    .0492465
                         |
                   yprcp |   .0001682   .0002739     0.61   0.539    -.0003689    .0007053
                    ytav |   .2357466    .158633     1.49   0.137    -.0753542    .5468474
                  ydda29 |  -.0054871   .0031426    -1.75   0.081    -.0116502    .0006759
                  yddb10 |   .0000639   .0006857     0.09   0.926    -.0012809    .0014087
                         |
      c.year#c.lnpop1940 |  -.2283618   .1161186    -1.97   0.049    -.4560861   -.0006375
                         |
      c.year#c.lnemp1940 |   .3628387   .1143805     3.17   0.002      .138523    .5871543
                         |
      c.year#c.lnmfg1940 |   -.112581   .0180896    -6.22   0.000    -.1480571   -.0771049
                         |
      c.year#c.railroads |  -.0001237   .0001754    -0.71   0.481    -.0004676    .0002202
                         |
       c.year#c.inst1944 |  -.0285676   .0252256    -1.13   0.258    -.0780385    .0209032
                         |
         cap30mile_hydro |   .0674742   .0654298     1.03   0.303    -.0608425    .1957909
       cap30mileH2wlight |   .2002005   .0298635     6.70   0.000     .1416341    .2587669
       cap30mileL2wlight |   .1380196   .0544432     2.54   0.011     .0312492    .2447901
amdiarrcap30milelightL2w |  -.2315147   .0707099    -3.27   0.001    -.3701863   -.0928431
                   _cons |   1175.627   1585.017     0.74   0.458    -1932.806     4284.06
------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileH2wlight cap30mileL2wlight amdiarrcap30milelightL2w) nocons /*
> */ ctitle(T4_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mileH2wlight cap30mileL2wlight cap30mileL2wlightH2wcoalstove /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  15,   2026) =      14.11
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6794
                                                  Adj R-squared   =     0.6794
                                                  Within R-sq.    =     0.0256
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8816

                                         (Std. Err. adjusted for 2,027 clusters in county_fips)
-----------------------------------------------------------------------------------------------
                              |               Robust
                          imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
------------------------------+----------------------------------------------------------------
                c.year#c.laty |   .0557803   .0123214     4.53   0.000     .0316163    .0799444
                              |
                c.year#c.lony |   .0344823   .0079567     4.33   0.000     .0188782    .0500865
                              |
                        yprcp |   .0001767   .0002729     0.65   0.517    -.0003585    .0007119
                         ytav |   .2297528   .1574493     1.46   0.145    -.0790267    .5385322
                       ydda29 |   -.005273   .0031291    -1.69   0.092    -.0114095    .0008635
                       yddb10 |    .000046   .0006833     0.07   0.946    -.0012939     .001386
                              |
           c.year#c.lnpop1940 |  -.2188512    .116388    -1.88   0.060    -.4471038    .0094015
                              |
           c.year#c.lnemp1940 |   .3544579   .1144906     3.10   0.002     .1299264    .5789894
                              |
           c.year#c.lnmfg1940 |  -.1118783   .0181387    -6.17   0.000    -.1474508   -.0763058
                              |
           c.year#c.railroads |  -.0001095   .0001743    -0.63   0.530    -.0004514    .0002323
                              |
            c.year#c.inst1944 |  -.0312681   .0253259    -1.23   0.217    -.0809357    .0183995
                              |
              cap30mile_hydro |   .0566537   .0655519     0.86   0.388    -.0719025    .1852099
            cap30mileH2wlight |   .1946169    .029672     6.56   0.000     .1364262    .2528077
            cap30mileL2wlight |   .0791832   .0588985     1.34   0.179    -.0363247    .1946911
cap30mileL2wlightH2wcoalstove |  -.1435259   .0814893    -1.76   0.078    -.3033375    .0162857
                        _cons |    1295.86   1586.453     0.82   0.414    -1815.389     4407.11
-----------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileH2wlight cap30mileL2wlight cap30mileL2wlightH2wcoalstove) nocons /*
> */ ctitle(T4_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***BOTTOM ROWS
. ****************************************
. *for columns 1-3
. reghdfe elecgasstove /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30mileH2wlight cap30mileL2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ , absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 3 iterations)

HDFE Linear regression                            Number of obs   =      5,876
Absorbing 2 HDFE groups                           F(  14,   1958) =     124.77
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9485
                                                  Adj R-squared   =     0.9224
                                                  Within R-sq.    =     0.3528
Number of clusters (county_fips) =      1,959     Root MSE        =     9.1467

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
      elecgasstove |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   -.020956   .0037705    -5.56   0.000    -.0283506   -.0135614
                   |
      c.year#c.lon |   .0085369   .0034163     2.50   0.013     .0018369    .0152368
                   |
            yprcpm |  -.0069871   .0019103    -3.66   0.000    -.0107335   -.0032407
             ytavm |  -5.427479   .6201238    -8.75   0.000    -6.643651   -4.211307
           ydda29m |   .0140912   .0175944     0.80   0.423    -.0204144    .0485969
           yddb10m |  -.0276863   .0028672    -9.66   0.000    -.0333094   -.0220632
                   |
c.year#c.lnpop1940 |  -.3071043   .1271616    -2.42   0.016    -.5564905   -.0577181
                   |
c.year#c.lnemp1940 |  -.0974272   .1132718    -0.86   0.390    -.3195731    .1247187
                   |
c.year#c.lnmfg1940 |  -.1514017   .0214804    -7.05   0.000    -.1935285   -.1092748
                   |
c.year#c.railroads |   .0004775    .000433     1.10   0.270    -.0003718    .0013267
                   |
 c.year#c.inst1944 |  -.0209726   .0360177    -0.58   0.560    -.0916097    .0496645
                   |
   cap30mile_hydro |   1.474383   .5425781     2.72   0.007     .4102912    2.538474
 cap30mileH2wlight |  -.6752573   .1188525    -5.68   0.000    -.9083479   -.4421667
 cap30mileL2wlight |   .1886019   .1064129     1.77   0.076    -.0200927    .3972964
             _cons |   12871.99   1011.022    12.73   0.000      10889.2    14854.78
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. *number of observations
. di e(N)
5876

. 
. *number of counties
. di e(N_clust) 
1959

. 
. 
. *for columns 4-5
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mileH2wlight cap30mileL2wlight amdiarrcap30milelightL2w /*
> */ , absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(dropped 25 singleton observations)
(MWFE estimator converged in 2 iterations)

HDFE Linear regression                            Number of obs   =     50,650
Absorbing 2 HDFE groups                           F(  15,   2025) =      15.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.4750
                                                  Adj R-squared   =     0.4409
                                                  Within R-sq.    =     0.0133
Number of clusters (county_fips) =      2,026     Root MSE        =    10.2651

                                    (Std. Err. adjusted for 2,026 clusters in county_fips)
------------------------------------------------------------------------------------------
                         |               Robust
                     imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------------+----------------------------------------------------------------
           c.year#c.laty |   .0375525   .0112961     3.32   0.001     .0153992    .0597057
                         |
           c.year#c.lony |    .014443   .0077695     1.86   0.063     -.000794      .02968
                         |
                   yprcp |    .000061   .0003307     0.18   0.854    -.0005876    .0007095
                    ytav |  -.1038262   .1646465    -0.63   0.528    -.4267204     .219068
                  ydda29 |  -.0022136   .0047559    -0.47   0.642    -.0115405    .0071134
                  yddb10 |  -.0008859    .000752    -1.18   0.239    -.0023607     .000589
                         |
      c.year#c.lnpop1940 |  -.3884303   .1246547    -3.12   0.002    -.6328951   -.1439654
                         |
      c.year#c.lnemp1940 |   .2946494   .1216687     2.42   0.016     .0560405    .5332583
                         |
      c.year#c.lnmfg1940 |  -.0813284   .0164235    -4.95   0.000    -.1135371   -.0491197
                         |
      c.year#c.railroads |   .0002895    .000231     1.25   0.210    -.0001635    .0007424
                         |
       c.year#c.inst1944 |  -.0035603   .0230245    -0.15   0.877    -.0487144    .0415938
                         |
         cap30mile_hydro |   -.196904   .2794121    -0.70   0.481    -.7448692    .3510613
       cap30mileH2wlight |   .4957739   .0568488     8.72   0.000     .3842857    .6072621
       cap30mileL2wlight |   .3457631   .0910184     3.80   0.000     .1672636    .5242627
amdiarrcap30milelightL2w |  -.3490726   .1033214    -3.38   0.001       -.5517   -.1464453
                   _cons |   3210.558   1619.984     1.98   0.048     33.54962    6387.567
------------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2026        2026           0    *|
   state_fips#year |      1050           0        1050     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. 
. *number of observations
. di e(N)
50650

. 
. *number of counties
. di e(N_clust) 
2026

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***TABLE 5
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. global Geo c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. global Geo3 c.year#c.lat c.year#c.lon yprcpm ytavm ydda29m yddb10m

. 
. global Econ c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. global Econ3nln c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. ****************************************
. ***PANEL A
. ****************************************
. reghdfe imr /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      23.41
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7406
                                                  Adj R-squared   =     0.7405
                                                  Within R-sq.    =     0.0671
Number of clusters (county_fips) =      1,959     Root MSE        =     5.7835

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   .0224424   .0047183     4.76   0.000      .013189    .0316958
                   |
      c.year#c.lon |   -.002161   .0033422    -0.65   0.518    -.0087155    .0043936
                   |
            yprcpm |  -.0045046   .0026843    -1.68   0.093     -.009769    .0007599
             ytavm |   .4354115   1.147029     0.38   0.704    -1.814114    2.684937
           ydda29m |  -.0268069   .0281153    -0.95   0.340    -.0819459    .0283321
           yddb10m |  -.0005759   .0041838    -0.14   0.891     -.008781    .0076292
                   |
c.year#c.lnpop1940 |   -.511812   .1727572    -2.96   0.003    -.8506194   -.1730046
                   |
c.year#c.lnemp1940 |   .5473366   .1793882     3.05   0.002     .1955247    .8991484
                   |
c.year#c.lnmfg1940 |  -.0764701   .0288314    -2.65   0.008    -.1330135   -.0199267
                   |
c.year#c.railroads |   .0002889   .0002793     1.03   0.301    -.0002589    .0008366
                   |
 c.year#c.inst1944 |  -.0383436   .0391958    -0.98   0.328    -.1152133    .0385262
                   |
   cap30mile_hydro |  -.4931168   .5557723    -0.89   0.375    -1.583084    .5968506
 scap1940cap30mile |  -.1486584   .1008715    -1.47   0.141    -.3464851    .0491683
 bcap1940cap30mile |   .2747173   .0720752     3.81   0.000     .1333652    .4160694
             _cons |  -403.5232   1054.984    -0.38   0.702    -2472.533    1665.487
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T5_PA_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmvhouse_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,347,968
Absorbing 2 HDFE groups                           F(  14,   1958) =      32.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9642
                                                  Adj R-squared   =     0.9642
                                                  Within R-sq.    =     0.2910
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1041

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
   lnmvhouse_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0010014   .0001327    -7.55   0.000    -.0012616   -.0007412
                   |
      c.year#c.lon |  -.0005583   .0000872    -6.40   0.000    -.0007293   -.0003873
                   |
            yprcpm |   .0001514   .0000394     3.84   0.000     .0000741    .0002286
             ytavm |   .0097467   .0153832     0.63   0.526    -.0204225    .0399158
           ydda29m |  -.0009042   .0006816    -1.33   0.185    -.0022409    .0004325
           yddb10m |   .0001495   .0000688     2.17   0.030     .0000146    .0002845
                   |
  c.year#c.pop1940 |  -4.12e-08   2.35e-08    -1.75   0.080    -8.73e-08    4.94e-09
                   |
  c.year#c.emp1940 |   7.39e-08   7.11e-08     1.04   0.299    -6.55e-08    2.13e-07
                   |
  c.year#c.mfg1940 |   9.40e-08   4.41e-08     2.13   0.033     7.43e-09    1.81e-07
                   |
c.year#c.railroads |   2.30e-06   8.53e-06     0.27   0.788    -.0000144     .000019
                   |
 c.year#c.inst1944 |  -.0059959   .0009789    -6.12   0.000    -.0079158   -.0040761
                   |
   cap30mile_hydro |   .0213075   .0144334     1.48   0.140     -.006999    .0496139
 scap1940cap30mile |   .0013405   .0031544     0.42   0.671    -.0048459    .0075269
 bcap1940cap30mile |  -.0028245   .0012345    -2.29   0.022    -.0052455   -.0004035
             _cons |   1.227126   16.50539     0.07   0.941    -31.14285     33.5971
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T5_PA_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnemp /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      23.16
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9948
                                                  Adj R-squared   =     0.9948
                                                  Within R-sq.    =     0.2430
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1283

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnemp |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0000395    .000145    -0.27   0.785    -.0003238    .0002448
                   |
      c.year#c.lon |  -.0003298   .0001216    -2.71   0.007    -.0005683   -.0000913
                   |
            yprcpm |  -.0000138   .0000733    -0.19   0.851    -.0001575    .0001299
             ytavm |   .0635118   .0233349     2.72   0.007      .017748    .1092757
           ydda29m |   .0030846    .000671     4.60   0.000     .0017686    .0044005
           yddb10m |   .0000696   .0000911     0.76   0.445     -.000109    .0002482
                   |
  c.year#c.pop1940 |   1.49e-08   2.40e-08     0.62   0.535    -3.22e-08    6.20e-08
                   |
  c.year#c.emp1940 |  -3.62e-08   6.62e-08    -0.55   0.584    -1.66e-07    9.36e-08
                   |
  c.year#c.mfg1940 |  -8.17e-08   3.55e-08    -2.30   0.022    -1.51e-07   -1.21e-08
                   |
c.year#c.railroads |   .0000274   9.15e-06     2.99   0.003     9.41e-06    .0000453
                   |
 c.year#c.inst1944 |   .0096185   .0015653     6.14   0.000     .0065487    .0126883
                   |
   cap30mile_hydro |  -.0175282   .0122771    -1.43   0.154    -.0416057    .0065494
 scap1940cap30mile |   .0163524   .0084947     1.93   0.054    -.0003072    .0330121
 bcap1940cap30mile |   .0096602   .0032507     2.97   0.003      .003285    .0160354
             _cons |  -56.20495   24.54284    -2.29   0.022    -104.3378   -8.072116
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T5_PA_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmfg /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      59.80
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9929
                                                  Adj R-squared   =     0.9929
                                                  Within R-sq.    =     0.2687
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1895

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnmfg |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0004156   .0001907    -2.18   0.029    -.0007895   -.0000417
                   |
      c.year#c.lon |  -.0010756   .0001561    -6.89   0.000    -.0013818   -.0007694
                   |
            yprcpm |   .0000934   .0000861     1.08   0.278    -.0000755    .0002622
             ytavm |   .0529319   .0307322     1.72   0.085    -.0073393     .113203
           ydda29m |   .0028589   .0008268     3.46   0.001     .0012374    .0044804
           yddb10m |   -.000012   .0001406    -0.09   0.932    -.0002879    .0002638
                   |
  c.year#c.pop1940 |  -1.51e-08   2.79e-08    -0.54   0.589    -6.97e-08    3.96e-08
                   |
  c.year#c.emp1940 |   4.60e-08   8.32e-08     0.55   0.580    -1.17e-07    2.09e-07
                   |
  c.year#c.mfg1940 |  -1.10e-07   4.08e-08    -2.69   0.007    -1.90e-07   -2.96e-08
                   |
c.year#c.railroads |   9.14e-06   .0000114     0.80   0.422    -.0000132    .0000314
                   |
 c.year#c.inst1944 |   -.004716   .0021898    -2.15   0.031    -.0090107   -.0004214
                   |
   cap30mile_hydro |  -.0492423   .0229103    -2.15   0.032    -.0941733   -.0043112
 scap1940cap30mile |   .0215712   .0106302     2.03   0.043     .0007235     .042419
 bcap1940cap30mile |   .0067836   .0035326     1.92   0.055    -.0001446    .0137117
             _cons |  -127.6439   31.22433    -4.09   0.000    -188.8804   -66.40754
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T5_PA_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmfgwages_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,106,292
Absorbing 2 HDFE groups                           F(  14,   1907) =      17.51
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9554
                                                  Adj R-squared   =     0.9554
                                                  Within R-sq.    =     0.0741
Number of clusters (county_fips) =      1,908     Root MSE        =     0.0925

                              (Std. Err. adjusted for 1,908 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
  lnmfgwages_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   -.000647   .0000864    -7.49   0.000    -.0008164   -.0004777
                   |
      c.year#c.lon |   .0000559   .0000462     1.21   0.227    -.0000347    .0001466
                   |
            yprcpm |   .0000301    .000032     0.94   0.347    -.0000327    .0000929
             ytavm |   .0241721   .0108482     2.23   0.026     .0028966    .0454476
           ydda29m |   -.000124   .0003844    -0.32   0.747     -.000878      .00063
           yddb10m |    .000157   .0000558     2.81   0.005     .0000476    .0002665
                   |
  c.year#c.pop1940 |  -1.50e-08   9.18e-09    -1.63   0.103    -3.30e-08    3.03e-09
                   |
  c.year#c.emp1940 |   3.20e-08   2.72e-08     1.18   0.239    -2.13e-08    8.54e-08
                   |
  c.year#c.mfg1940 |   1.41e-08   1.65e-08     0.85   0.394    -1.83e-08    4.65e-08
                   |
c.year#c.railroads |  -2.45e-06   4.76e-06    -0.52   0.606    -.0000118    6.87e-06
                   |
 c.year#c.inst1944 |  -.0002239   .0005946    -0.38   0.707    -.0013901    .0009422
                   |
   cap30mile_hydro |   .0031261   .0077902     0.40   0.688    -.0121521    .0184043
 scap1940cap30mile |   .0017495    .001717     1.02   0.308    -.0016179    .0051169
 bcap1940cap30mile |   -.001746   .0006442    -2.71   0.007    -.0030095   -.0004825
             _cons |    63.2506   10.47703     6.04   0.000     42.70296    83.79825
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1908        1908           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T5_PA_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnretwages_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,347,612
Absorbing 2 HDFE groups                           F(  14,   1958) =      48.76
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9468
                                                  Adj R-squared   =     0.9467
                                                  Within R-sq.    =     0.2254
Number of clusters (county_fips) =      1,959     Root MSE        =     0.0642

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
  lnretwages_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0005391   .0000566    -9.52   0.000    -.0006501   -.0004281
                   |
      c.year#c.lon |  -.0000606   .0000315    -1.92   0.054    -.0001224    1.15e-06
                   |
            yprcpm |   .0000515   .0000205     2.51   0.012     .0000113    .0000917
             ytavm |  -.0227397   .0075113    -3.03   0.002    -.0374707   -.0080088
           ydda29m |   -.000941   .0002831    -3.32   0.001    -.0014962   -.0003857
           yddb10m |  -.0000419    .000032    -1.31   0.190    -.0001046    .0000208
                   |
  c.year#c.pop1940 |  -2.86e-08   6.86e-09    -4.16   0.000    -4.20e-08   -1.51e-08
                   |
  c.year#c.emp1940 |   7.26e-08   1.97e-08     3.69   0.000     3.40e-08    1.11e-07
                   |
  c.year#c.mfg1940 |  -4.06e-09   1.05e-08    -0.39   0.698    -2.46e-08    1.65e-08
                   |
c.year#c.railroads |  -4.20e-07   2.75e-06    -0.15   0.879    -5.82e-06    4.98e-06
                   |
 c.year#c.inst1944 |  -.0026312   .0004532    -5.81   0.000    -.0035201   -.0017423
                   |
   cap30mile_hydro |   .0154796   .0052328     2.96   0.003     .0052172    .0257419
 scap1940cap30mile |  -.0016803   .0009429    -1.78   0.075    -.0035294    .0001688
 bcap1940cap30mile |  -.0021464   .0003311    -6.48   0.000    -.0027958    -.001497
             _cons |   38.75793   7.033638     5.51   0.000     24.96373    52.55214
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T5_PA_c6) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe pwhite /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      16.18
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9431
                                                  Adj R-squared   =     0.9430
                                                  Within R-sq.    =     0.1740
Number of clusters (county_fips) =      1,959     Root MSE        =     3.2305

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
            pwhite |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0215083   .0024918    -8.63   0.000    -.0263952   -.0166214
                   |
      c.year#c.lon |   .0027853   .0020246     1.38   0.169    -.0011852    .0067559
                   |
            yprcpm |   .0015463   .0010559     1.46   0.143    -.0005246    .0036172
             ytavm |   -1.03069   .4957898    -2.08   0.038    -2.003021   -.0583589
           ydda29m |   .0254719   .0157529     1.62   0.106    -.0054223    .0563662
           yddb10m |   -.004844   .0019159    -2.53   0.012    -.0086013   -.0010866
                   |
c.year#c.lnpop1940 |  -.0696535   .1676672    -0.42   0.678    -.3984784    .2591713
                   |
c.year#c.lnemp1940 |   -.101394   .1887931    -0.54   0.591    -.4716506    .2688626
                   |
c.year#c.lnmfg1940 |   .0477593   .0356881     1.34   0.181    -.0222315      .11775
                   |
c.year#c.railroads |   .0004261   .0002112     2.02   0.044     .0000119    .0008403
                   |
 c.year#c.inst1944 |   .0462321   .0207185     2.23   0.026     .0055995    .0868648
                   |
   cap30mile_hydro |    .276168   .2326686     1.19   0.235    -.1801362    .7324722
 scap1940cap30mile |   .0606019   .0561338     1.08   0.280    -.0494864    .1706903
 bcap1940cap30mile |  -.0455581   .0364643    -1.25   0.212     -.117071    .0259548
             _cons |    4902.95   714.4626     6.86   0.000     3501.763    6304.137
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T5_PA_c7) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe phschool /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      38.29
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9755
                                                  Adj R-squared   =     0.9755
                                                  Within R-sq.    =     0.2003
Number of clusters (county_fips) =      1,959     Root MSE        =     1.8599

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
          phschool |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   .0170942   .0016146    10.59   0.000     .0139278    .0202607
                   |
      c.year#c.lon |   .0014675   .0011348     1.29   0.196    -.0007581    .0036931
                   |
            yprcpm |  -.0029264   .0011091    -2.64   0.008    -.0051016   -.0007512
             ytavm |  -1.595526   .3826412    -4.17   0.000    -2.345953   -.8450995
           ydda29m |   .0100877   .0079302     1.27   0.204    -.0054649    .0256403
           yddb10m |  -.0108367   .0014331    -7.56   0.000    -.0136473   -.0080261
                   |
c.year#c.lnpop1940 |  -.2161563   .0556202    -3.89   0.000    -.3252373   -.1070752
                   |
c.year#c.lnemp1940 |   .1200974   .0633939     1.89   0.058    -.0042292    .2444241
                   |
c.year#c.lnmfg1940 |   .0422071   .0147069     2.87   0.004     .0133643    .0710499
                   |
c.year#c.railroads |   .0003608   .0000938     3.85   0.000     .0001769    .0005447
                   |
 c.year#c.inst1944 |    .058833   .0175178     3.36   0.001     .0244774    .0931886
                   |
   cap30mile_hydro |  -.4894614    .254971    -1.92   0.055    -.9895045    .0105816
 scap1940cap30mile |   .1099921   .0540302     2.04   0.042     .0040292    .2159549
 bcap1940cap30mile |  -.0480666   .0361125    -1.33   0.183    -.1188896    .0227564
             _cons |   549.6968    365.157     1.51   0.132    -166.4405    1265.834
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons /*
> */ ctitle(T5_PA_c8) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL B
. ****************************************
. reghdfe imr /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      24.65
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7413
                                                  Adj R-squared   =     0.7412
                                                  Within R-sq.    =     0.0695
Number of clusters (county_fips) =      1,959     Root MSE        =     5.7761

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   .0187038   .0046635     4.01   0.000     .0095579    .0278497
                   |
      c.year#c.lon |  -.0011177   .0033529    -0.33   0.739    -.0076934     .005458
                   |
            yprcpm |  -.0048749   .0027556    -1.77   0.077     -.010279    .0005293
             ytavm |   .1011786   1.202386     0.08   0.933    -2.256913     2.45927
           ydda29m |  -.0210368   .0283793    -0.74   0.459    -.0766936      .03462
           yddb10m |  -.0019635    .004368    -0.45   0.653    -.0105299    .0066028
                   |
c.year#c.lnpop1940 |  -.5335154   .1703898    -3.13   0.002    -.8676798   -.1993511
                   |
c.year#c.lnemp1940 |   .5578898     .17783     3.14   0.002     .2091339    .9066458
                   |
c.year#c.lnmfg1940 |  -.0747101   .0292729    -2.55   0.011    -.1321194   -.0173007
                   |
c.year#c.railroads |     .00035   .0002621     1.34   0.182     -.000164    .0008639
                   |
 c.year#c.inst1944 |  -.0278194   .0392809    -0.71   0.479    -.1048561    .0492173
                   |
   cap30mile_hydro |   -.599034   .5536792    -1.08   0.279    -1.684897    .4868286
 cap30mileL2wlight |  -.1329053   .0938432    -1.42   0.157    -.3169483    .0511378
 cap30mileH2wlight |   .2920701   .0785601     3.72   0.000     .1379998    .4461404
             _cons |   276.9321   1078.888     0.26   0.797    -1838.957    2392.822
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T5_PB_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmvhouse_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,347,968
Absorbing 2 HDFE groups                           F(  14,   1958) =      29.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9642
                                                  Adj R-squared   =     0.9642
                                                  Within R-sq.    =     0.2903
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1042

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
   lnmvhouse_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0009683   .0001359    -7.12   0.000    -.0012348   -.0007017
                   |
      c.year#c.lon |  -.0005743   .0000857    -6.70   0.000    -.0007422   -.0004063
                   |
            yprcpm |   .0001539     .00004     3.85   0.000     .0000754    .0002323
             ytavm |   .0127407   .0155958     0.82   0.414    -.0178455    .0433269
           ydda29m |  -.0009365    .000688    -1.36   0.174    -.0022857    .0004127
           yddb10m |    .000163   .0000706     2.31   0.021     .0000246    .0003013
                   |
  c.year#c.pop1940 |  -4.03e-08   2.35e-08    -1.72   0.086    -8.63e-08    5.76e-09
                   |
  c.year#c.emp1940 |   7.08e-08   7.08e-08     1.00   0.318    -6.81e-08    2.10e-07
                   |
  c.year#c.mfg1940 |   9.58e-08   4.42e-08     2.17   0.030     9.03e-09    1.82e-07
                   |
c.year#c.railroads |   1.86e-06   8.62e-06     0.22   0.829     -.000015    .0000188
                   |
 c.year#c.inst1944 |  -.0060825   .0009801    -6.21   0.000    -.0080046   -.0041605
                   |
   cap30mile_hydro |   .0225319   .0142177     1.58   0.113    -.0053516    .0504154
 cap30mileL2wlight |   .0014041   .0023311     0.60   0.547    -.0031676    .0059758
 cap30mileH2wlight |  -.0026001   .0011832    -2.20   0.028    -.0049206   -.0002796
             _cons |  -3.745046   16.90987    -0.22   0.825    -36.90828    29.41819
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T5_PB_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnemp /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      22.61
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9948
                                                  Adj R-squared   =     0.9948
                                                  Within R-sq.    =     0.2432
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1283

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnemp |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0000151   .0001554    -0.10   0.922    -.0003199    .0002896
                   |
      c.year#c.lon |  -.0003394   .0001315    -2.58   0.010    -.0005973   -.0000815
                   |
            yprcpm |  -7.57e-06   .0000726    -0.10   0.917      -.00015    .0001349
             ytavm |   .0656385     .02482     2.64   0.008     .0169621    .1143149
           ydda29m |   .0030803   .0006727     4.58   0.000      .001761    .0043995
           yddb10m |   .0000714   .0000994     0.72   0.473    -.0001235    .0002662
                   |
  c.year#c.pop1940 |   1.76e-08   2.31e-08     0.76   0.446    -2.77e-08    6.29e-08
                   |
  c.year#c.emp1940 |  -4.38e-08   6.36e-08    -0.69   0.491    -1.68e-07    8.09e-08
                   |
  c.year#c.mfg1940 |  -7.89e-08   3.49e-08    -2.26   0.024    -1.47e-07   -1.05e-08
                   |
c.year#c.railroads |    .000028   8.96e-06     3.12   0.002     .0000104    .0000456
                   |
 c.year#c.inst1944 |   .0096066   .0015445     6.22   0.000     .0065775    .0126357
                   |
   cap30mile_hydro |  -.0172017   .0117176    -1.47   0.142     -.040182    .0057786
 cap30mileL2wlight |   .0163369     .00415     3.94   0.000      .008198    .0244758
 cap30mileH2wlight |   .0092512   .0034758     2.66   0.008     .0024346    .0160678
             _cons |  -60.06305   25.40209    -2.36   0.018     -109.881   -10.24508
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T5_PB_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmfg /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      59.48
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9929
                                                  Adj R-squared   =     0.9929
                                                  Within R-sq.    =     0.2694
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1894

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnmfg |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0003543    .000196    -1.81   0.071    -.0007386      .00003
                   |
      c.year#c.lon |  -.0011093   .0001723    -6.44   0.000    -.0014471   -.0007715
                   |
            yprcpm |   .0001036   .0000863     1.20   0.230    -.0000658    .0002729
             ytavm |   .0596905   .0331011     1.80   0.071    -.0052266    .1246076
           ydda29m |   .0028184   .0008421     3.35   0.001      .001167    .0044698
           yddb10m |   .0000116   .0001496     0.08   0.938    -.0002819     .000305
                   |
  c.year#c.pop1940 |  -1.08e-08   2.69e-08    -0.40   0.687    -6.35e-08    4.19e-08
                   |
  c.year#c.emp1940 |   3.28e-08   8.03e-08     0.41   0.683    -1.25e-07    1.90e-07
                   |
  c.year#c.mfg1940 |  -1.04e-07   4.13e-08    -2.51   0.012    -1.85e-07   -2.27e-08
                   |
c.year#c.railroads |   9.72e-06   .0000108     0.90   0.369    -.0000115    .0000309
                   |
 c.year#c.inst1944 |  -.0048574    .002132    -2.28   0.023    -.0090386   -.0006762
                   |
   cap30mile_hydro |  -.0459987   .0222185    -2.07   0.039     -.089573   -.0024244
 cap30mileL2wlight |   .0191091   .0057429     3.33   0.001     .0078463    .0303719
 cap30mileH2wlight |   .0067659   .0038988     1.74   0.083    -.0008803     .014412
             _cons |  -138.0754   32.19221    -4.29   0.000      -201.21    -74.9408
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T5_PB_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmfgwages_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,106,292
Absorbing 2 HDFE groups                           F(  14,   1907) =      17.14
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9553
                                                  Adj R-squared   =     0.9553
                                                  Within R-sq.    =     0.0726
Number of clusters (county_fips) =      1,908     Root MSE        =     0.0926

                              (Std. Err. adjusted for 1,908 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
  lnmfgwages_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0006512   .0000903    -7.21   0.000    -.0008283   -.0004742
                   |
      c.year#c.lon |   .0000474   .0000481     0.99   0.325     -.000047    .0001418
                   |
            yprcpm |   .0000304   .0000324     0.94   0.349    -.0000332    .0000939
             ytavm |   .0255829   .0111996     2.28   0.022     .0036181    .0475477
           ydda29m |  -.0001239   .0003876    -0.32   0.749    -.0008841    .0006362
           yddb10m |   .0001666   .0000574     2.90   0.004      .000054    .0002793
                   |
  c.year#c.pop1940 |  -1.47e-08   9.03e-09    -1.63   0.103    -3.24e-08    2.97e-09
                   |
  c.year#c.emp1940 |   3.04e-08   2.68e-08     1.13   0.257    -2.21e-08    8.29e-08
                   |
  c.year#c.mfg1940 |   1.52e-08   1.66e-08     0.92   0.358    -1.73e-08    4.77e-08
                   |
c.year#c.railroads |  -1.97e-06   4.87e-06    -0.40   0.686    -.0000115    7.58e-06
                   |
 c.year#c.inst1944 |  -.0002825   .0006016    -0.47   0.639    -.0014623    .0008973
                   |
   cap30mile_hydro |   .0057677   .0078789     0.73   0.464    -.0096845      .02122
 cap30mileL2wlight |  -.0017099   .0013105    -1.30   0.192    -.0042801    .0008603
 cap30mileH2wlight |     -.0014   .0006804    -2.06   0.040    -.0027343   -.0000657
             _cons |   62.29395   10.97556     5.68   0.000     40.76859     83.8193
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1908        1908           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T5_PB_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnretwages_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,347,612
Absorbing 2 HDFE groups                           F(  14,   1958) =      55.33
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9470
                                                  Adj R-squared   =     0.9469
                                                  Within R-sq.    =     0.2282
Number of clusters (county_fips) =      1,959     Root MSE        =     0.0641

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
  lnretwages_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0005031    .000059    -8.53   0.000    -.0006187   -.0003875
                   |
      c.year#c.lon |  -.0000665   .0000307    -2.17   0.030    -.0001266   -6.32e-06
                   |
            yprcpm |   .0000535   .0000205     2.60   0.009     .0000132    .0000938
             ytavm |  -.0211459   .0073218    -2.89   0.004    -.0355053   -.0067865
           ydda29m |  -.0009803   .0002804    -3.50   0.000    -.0015302   -.0004304
           yddb10m |  -.0000377   .0000312    -1.21   0.228    -.0000988    .0000235
                   |
  c.year#c.pop1940 |  -2.81e-08   6.75e-09    -4.17   0.000    -4.14e-08   -1.49e-08
                   |
  c.year#c.emp1940 |   7.20e-08   1.93e-08     3.74   0.000     3.42e-08    1.10e-07
                   |
  c.year#c.mfg1940 |  -3.67e-09   1.06e-08    -0.35   0.730    -2.45e-08    1.72e-08
                   |
c.year#c.railroads |  -1.44e-06   2.75e-06    -0.52   0.600    -6.84e-06    3.95e-06
                   |
 c.year#c.inst1944 |  -.0026529    .000453    -5.86   0.000    -.0035412   -.0017645
                   |
   cap30mile_hydro |   .0146688   .0050881     2.88   0.004     .0046901    .0246475
 cap30mileL2wlight |    .001363   .0008261     1.65   0.099    -.0002572    .0029832
 cap30mileH2wlight |  -.0023582   .0003441    -6.85   0.000    -.0030331   -.0016833
             _cons |   35.12631    7.09187     4.95   0.000      21.2179    49.03471
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T5_PB_c6) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe pwhite /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      17.21
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9433
                                                  Adj R-squared   =     0.9433
                                                  Within R-sq.    =     0.1769
Number of clusters (county_fips) =      1,959     Root MSE        =     3.2248

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
            pwhite |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0199116   .0025595    -7.78   0.000    -.0249312    -.014892
                   |
      c.year#c.lon |   .0023933    .001994     1.20   0.230    -.0015173    .0063038
                   |
            yprcpm |   .0016872    .001057     1.60   0.111    -.0003859    .0037602
             ytavm |  -.9117942   .5043743    -1.81   0.071    -1.900961    .0773727
           ydda29m |   .0230872   .0159225     1.45   0.147    -.0081398    .0543141
           yddb10m |   -.004415    .001952    -2.26   0.024    -.0082431   -.0005868
                   |
c.year#c.lnpop1940 |  -.0639321   .1664227    -0.38   0.701    -.3903164    .2624522
                   |
c.year#c.lnemp1940 |  -.1011521   .1877779    -0.54   0.590    -.4694175    .2671134
                   |
c.year#c.lnmfg1940 |   .0466769    .035672     1.31   0.191    -.0232822     .116636
                   |
c.year#c.railroads |   .0004035   .0002077     1.94   0.052    -3.90e-06    .0008109
                   |
 c.year#c.inst1944 |   .0413138   .0204226     2.02   0.043     .0012614    .0813661
                   |
   cap30mile_hydro |   .2782548   .2244941     1.24   0.215    -.1620177    .7185272
 cap30mileL2wlight |   .1347468   .0470035     2.87   0.004     .0425646     .226929
 cap30mileH2wlight |  -.0543224   .0372038    -1.46   0.144    -.1272857    .0186409
             _cons |    4609.29   709.7346     6.49   0.000     3217.375    6001.205
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T5_PB_c7) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe phschool /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      35.99
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9757
                                                  Adj R-squared   =     0.9757
                                                  Within R-sq.    =     0.2074
Number of clusters (county_fips) =      1,959     Root MSE        =     1.8515

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
          phschool |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   .0186309    .001677    11.11   0.000     .0153419    .0219199
                   |
      c.year#c.lon |   .0011169   .0012038     0.93   0.354    -.0012441    .0034778
                   |
            yprcpm |  -.0027557   .0010825    -2.55   0.011    -.0048788   -.0006327
             ytavm |  -1.455565   .3893107    -3.74   0.000    -2.219072   -.6920586
           ydda29m |   .0073609   .0081027     0.91   0.364    -.0085299    .0232517
           yddb10m |  -.0103122   .0014754    -6.99   0.000    -.0132057   -.0074187
                   |
c.year#c.lnpop1940 |  -.2079622   .0546328    -3.81   0.000    -.3151066   -.1008177
                   |
c.year#c.lnemp1940 |   .1189321   .0632762     1.88   0.060    -.0051638     .243028
                   |
c.year#c.lnmfg1940 |   .0409781   .0148642     2.76   0.006     .0118268    .0701294
                   |
c.year#c.railroads |    .000341   .0000961     3.55   0.000     .0001525    .0005294
                   |
 c.year#c.inst1944 |   .0538013   .0175468     3.07   0.002      .019389    .0882136
                   |
   cap30mile_hydro |  -.4630313   .2544192    -1.82   0.069    -.9619923    .0359297
 cap30mileL2wlight |   .1264351   .0383055     3.30   0.001     .0513112    .2015589
 cap30mileH2wlight |  -.0631551   .0352151    -1.79   0.073    -.1322181     .005908
             _cons |   241.5164   374.7735     0.64   0.519    -493.4805    976.5133
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(T5_PB_c8) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL C
. ****************************************
. reghdfe imr /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      23.33
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7408
                                                  Adj R-squared   =     0.7408
                                                  Within R-sq.    =     0.0680
Number of clusters (county_fips) =      1,959     Root MSE        =     5.7808

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   .0222974   .0047318     4.71   0.000     .0130176    .0315772
                   |
      c.year#c.lon |  -.0024314    .003338    -0.73   0.466    -.0089779    .0041151
                   |
            yprcpm |  -.0048826   .0027312    -1.79   0.074     -.010239    .0004737
             ytavm |   .5025044   1.159691     0.43   0.665    -1.771854    2.776863
           ydda29m |  -.0267308    .028074    -0.95   0.341    -.0817889    .0283273
           yddb10m |  -.0003273   .0042372    -0.08   0.938    -.0086372    .0079825
                   |
c.year#c.lnpop1940 |  -.5077932    .171855    -2.95   0.003    -.8448311   -.1707553
                   |
c.year#c.lnemp1940 |     .54448   .1787872     3.05   0.002     .1938467    .8951133
                   |
c.year#c.lnmfg1940 |  -.0785561     .02877    -2.73   0.006    -.1349792    -.022133
                   |
c.year#c.railroads |   .0002546   .0002865     0.89   0.374    -.0003073    .0008165
                   |
 c.year#c.inst1944 |  -.0350533   .0391472    -0.90   0.371    -.1118279    .0417213
                   |
   cap30mile_hydro |  -.3680994   .5576056    -0.66   0.509    -1.461662    .7254635
cap30milecapdop10l |  -.2152097   .0951943    -2.26   0.024    -.4019025    -.028517
cap30milecapdop10m |   .2855541    .073283     3.90   0.000     .1418332    .4292751
             _cons |  -428.2133   1057.831    -0.40   0.686    -2502.806    1646.379
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T5_PC_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmvhouse_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,347,968
Absorbing 2 HDFE groups                           F(  14,   1958) =      30.68
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9642
                                                  Adj R-squared   =     0.9642
                                                  Within R-sq.    =     0.2899
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1042

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
   lnmvhouse_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |   -.001006   .0001346    -7.47   0.000      -.00127    -.000742
                   |
      c.year#c.lon |  -.0005627   .0000871    -6.46   0.000    -.0007336   -.0003918
                   |
            yprcpm |    .000153   .0000402     3.80   0.000     .0000741    .0002318
             ytavm |   .0107766   .0154909     0.70   0.487    -.0196038     .041157
           ydda29m |  -.0009026   .0006881    -1.31   0.190    -.0022521     .000447
           yddb10m |   .0001562   .0000688     2.27   0.023     .0000212    .0002912
                   |
  c.year#c.pop1940 |  -4.06e-08   2.34e-08    -1.73   0.083    -8.66e-08    5.35e-09
                   |
  c.year#c.emp1940 |   7.16e-08   7.07e-08     1.01   0.312    -6.71e-08    2.10e-07
                   |
  c.year#c.mfg1940 |   9.49e-08   4.41e-08     2.15   0.032     8.40e-09    1.81e-07
                   |
c.year#c.railroads |   2.95e-06   8.63e-06     0.34   0.733     -.000014    .0000199
                   |
 c.year#c.inst1944 |  -.0060311   .0009717    -6.21   0.000    -.0079367   -.0041255
                   |
   cap30mile_hydro |   .0227309   .0143969     1.58   0.115     -.005504    .0509658
cap30milecapdop10l |  -.0014629   .0025564    -0.57   0.567    -.0064764    .0035507
cap30milecapdop10m |  -.0026427   .0012277    -2.15   0.031    -.0050504    -.000235
             _cons |   .8357971   16.49889     0.05   0.960    -31.52144    33.19303
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T5_PC_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnemp /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      23.25
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9948
                                                  Adj R-squared   =     0.9948
                                                  Within R-sq.    =     0.2424
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1284

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnemp |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0000393   .0001455    -0.27   0.787    -.0003247    .0002461
                   |
      c.year#c.lon |  -.0003272   .0001201    -2.72   0.007    -.0005628   -.0000916
                   |
            yprcpm |  -8.81e-06   .0000725    -0.12   0.903     -.000151    .0001334
             ytavm |    .063753   .0233873     2.73   0.006     .0178863    .1096196
           ydda29m |   .0030755   .0006703     4.59   0.000     .0017609      .00439
           yddb10m |   .0000722   .0000917     0.79   0.431    -.0001077     .000252
                   |
  c.year#c.pop1940 |   1.62e-08   2.43e-08     0.67   0.505    -3.15e-08    6.38e-08
                   |
  c.year#c.emp1940 |  -3.99e-08   6.68e-08    -0.60   0.551    -1.71e-07    9.12e-08
                   |
  c.year#c.mfg1940 |  -8.17e-08   3.53e-08    -2.32   0.021    -1.51e-07   -1.25e-08
                   |
c.year#c.railroads |   .0000283   8.98e-06     3.15   0.002     .0000107    .0000459
                   |
 c.year#c.inst1944 |   .0095865    .001551     6.18   0.000     .0065446    .0126283
                   |
   cap30mile_hydro |  -.0181959   .0131574    -1.38   0.167    -.0439998     .007608
cap30milecapdop10l |    .015812   .0094623     1.67   0.095    -.0027453    .0343693
cap30milecapdop10m |   .0096809   .0032444     2.98   0.003     .0033181    .0160438
             _cons |  -55.95243   24.48847    -2.28   0.022    -103.9786   -7.926224
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T5_PC_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmfg /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      58.16
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9929
                                                  Adj R-squared   =     0.9929
                                                  Within R-sq.    =     0.2711
Number of clusters (county_fips) =      1,959     Root MSE        =     0.1892

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnmfg |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0004037   .0001896    -2.13   0.033    -.0007756   -.0000318
                   |
      c.year#c.lon |  -.0010555   .0001526    -6.92   0.000    -.0013548   -.0007561
                   |
            yprcpm |   .0001081   .0000845     1.28   0.201    -.0000576    .0002738
             ytavm |   .0513628   .0306744     1.67   0.094     -.008795    .1115207
           ydda29m |   .0028215   .0008297     3.40   0.001     .0011943    .0044487
           yddb10m |  -.0000183   .0001412    -0.13   0.897    -.0002954    .0002587
                   |
  c.year#c.pop1940 |  -1.17e-08   2.79e-08    -0.42   0.675    -6.65e-08    4.30e-08
                   |
  c.year#c.emp1940 |   3.78e-08   8.31e-08     0.45   0.650    -1.25e-07    2.01e-07
                   |
  c.year#c.mfg1940 |  -1.12e-07   4.03e-08    -2.77   0.006    -1.91e-07   -3.25e-08
                   |
c.year#c.railroads |   .0000112   .0000111     1.01   0.315    -.0000106    .0000331
                   |
 c.year#c.inst1944 |  -.0047507   .0021698    -2.19   0.029     -.009006   -.0004953
                   |
   cap30mile_hydro |  -.0551058   .0236515    -2.33   0.020    -.1014906   -.0087209
cap30milecapdop10l |   .0262713   .0111862     2.35   0.019     .0043332    .0482093
cap30milecapdop10m |   .0064259   .0034832     1.84   0.065    -.0004052    .0132571
             _cons |  -125.7743   30.73124    -4.09   0.000    -186.0436   -65.50489
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T5_PC_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnmfgwages_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,106,292
Absorbing 2 HDFE groups                           F(  14,   1907) =      17.72
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9554
                                                  Adj R-squared   =     0.9554
                                                  Within R-sq.    =     0.0735
Number of clusters (county_fips) =      1,908     Root MSE        =     0.0925

                              (Std. Err. adjusted for 1,908 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
  lnmfgwages_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0006473   .0000877    -7.38   0.000    -.0008194   -.0004752
                   |
      c.year#c.lon |   .0000562   .0000461     1.22   0.224    -.0000343    .0001467
                   |
            yprcpm |   .0000326   .0000319     1.02   0.306    -.0000299    .0000952
             ytavm |   .0244188   .0108847     2.24   0.025     .0030716    .0457659
           ydda29m |  -.0001285   .0003854    -0.33   0.739    -.0008844    .0006273
           yddb10m |   .0001591   .0000558     2.85   0.004     .0000498    .0002685
                   |
  c.year#c.pop1940 |  -1.43e-08   9.01e-09    -1.59   0.112    -3.20e-08    3.33e-09
                   |
  c.year#c.emp1940 |   3.01e-08   2.67e-08     1.13   0.260    -2.22e-08    8.24e-08
                   |
  c.year#c.mfg1940 |   1.42e-08   1.65e-08     0.86   0.388    -1.81e-08    4.66e-08
                   |
c.year#c.railroads |  -1.93e-06   4.73e-06    -0.41   0.683    -.0000112    7.35e-06
                   |
 c.year#c.inst1944 |  -.0002431   .0005945    -0.41   0.683    -.0014091     .000923
                   |
   cap30mile_hydro |    .003159    .007756     0.41   0.684    -.0120521      .01837
cap30milecapdop10l |   .0011137   .0020487     0.54   0.587    -.0029041    .0051316
cap30milecapdop10m |   -.001707   .0006427    -2.66   0.008    -.0029674   -.0004466
             _cons |   63.24466   10.51811     6.01   0.000     42.61645    83.87288
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1908        1908           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T5_PC_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnretwages_bls90 /*
> */ $Geo3 $Econ3nln cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,347,612
Absorbing 2 HDFE groups                           F(  14,   1958) =      49.61
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9468
                                                  Adj R-squared   =     0.9467
                                                  Within R-sq.    =     0.2254
Number of clusters (county_fips) =      1,959     Root MSE        =     0.0642

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
  lnretwages_bls90 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0005394   .0000567    -9.52   0.000    -.0006506   -.0004283
                   |
      c.year#c.lon |   -.000061   .0000319    -1.91   0.056    -.0001235    1.56e-06
                   |
            yprcpm |   .0000517   .0000206     2.52   0.012     .0000114    .0000921
             ytavm |  -.0226506   .0075432    -3.00   0.003    -.0374441   -.0078571
           ydda29m |   -.000941   .0002835    -3.32   0.001    -.0014971    -.000385
           yddb10m |  -.0000413    .000032    -1.29   0.197    -.0001041    .0000215
                   |
  c.year#c.pop1940 |  -2.85e-08   6.84e-09    -4.16   0.000    -4.19e-08   -1.51e-08
                   |
  c.year#c.emp1940 |   7.24e-08   1.96e-08     3.69   0.000     3.39e-08    1.11e-07
                   |
  c.year#c.mfg1940 |  -4.00e-09   1.05e-08    -0.38   0.703    -2.45e-08    1.65e-08
                   |
c.year#c.railroads |  -3.48e-07   2.71e-06    -0.13   0.898    -5.66e-06    4.97e-06
                   |
 c.year#c.inst1944 |  -.0026346   .0004526    -5.82   0.000    -.0035223    -.001747
                   |
   cap30mile_hydro |   .0155838   .0052427     2.97   0.003      .005302    .0258657
cap30milecapdop10l |  -.0019208   .0010697    -1.80   0.073    -.0040187    .0001771
cap30milecapdop10m |  -.0021311   .0003292    -6.47   0.000    -.0027767   -.0014854
             _cons |   38.73031   7.052405     5.49   0.000      24.8993    52.56132
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T5_PC_c6) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe pwhite /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      15.63
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9430
                                                  Adj R-squared   =     0.9430
                                                  Within R-sq.    =     0.1737
Number of clusters (county_fips) =      1,959     Root MSE        =     3.2311

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
            pwhite |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |  -.0215191   .0024963    -8.62   0.000    -.0264148   -.0166234
                   |
      c.year#c.lon |   .0028128   .0020286     1.39   0.166    -.0011656    .0067912
                   |
            yprcpm |    .001627   .0010628     1.53   0.126    -.0004574    .0037113
             ytavm |  -1.043161   .4962511    -2.10   0.036    -2.016396   -.0699246
           ydda29m |    .025624   .0157534     1.63   0.104    -.0052713    .0565192
           yddb10m |  -.0048764   .0019187    -2.54   0.011    -.0086393   -.0011134
                   |
c.year#c.lnpop1940 |  -.0694138   .1677108    -0.41   0.679    -.3983242    .2594965
                   |
c.year#c.lnemp1940 |  -.1024866   .1888742    -0.54   0.587    -.4729023    .2679291
                   |
c.year#c.lnmfg1940 |   .0484062   .0356789     1.36   0.175    -.0215665    .1183789
                   |
c.year#c.railroads |   .0004325   .0002127     2.03   0.042     .0000154    .0008496
                   |
 c.year#c.inst1944 |   .0457073   .0206302     2.22   0.027     .0052477    .0861668
                   |
   cap30mile_hydro |    .264999   .2367258     1.12   0.263     -.199262      .72926
cap30milecapdop10l |   .0478761   .0572684     0.84   0.403    -.0644374    .1601896
cap30milecapdop10m |  -.0465668   .0371093    -1.25   0.210    -.1193446     .026211
             _cons |   4913.141   716.7669     6.85   0.000     3507.435    6318.848
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T5_PC_c7) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe phschool /*
> */ $Geo3 $Econ cap30mile_hydro /*
> */ cap30milecapdop10l cap30milecapdop10m /*
> */ if lnmrhouse_bls90~=. & N_mrhouse==3 /*
> */ [fw=births_rs], absorb(i.county_fips i.year) cluster(county_fips) 
(MWFE estimator converged in 4 iterations)

HDFE Linear regression                            Number of obs   =  7,348,786
Absorbing 2 HDFE groups                           F(  14,   1958) =      36.79
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.9754
                                                  Adj R-squared   =     0.9754
                                                  Within R-sq.    =     0.1992
Number of clusters (county_fips) =      1,959     Root MSE        =     1.8611

                              (Std. Err. adjusted for 1,959 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
          phschool |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
      c.year#c.lat |    .017101   .0016395    10.43   0.000     .0138856    .0203163
                   |
      c.year#c.lon |   .0015279   .0011311     1.35   0.177    -.0006903    .0037461
                   |
            yprcpm |  -.0027995   .0010999    -2.55   0.011    -.0049566   -.0006423
             ytavm |  -1.616196   .3774912    -4.28   0.000    -2.356523   -.8758694
           ydda29m |   .0102314   .0080248     1.27   0.202    -.0055067    .0259694
           yddb10m |  -.0108994    .001418    -7.69   0.000    -.0136803   -.0081184
                   |
c.year#c.lnpop1940 |   -.216402   .0551776    -3.92   0.000     -.324615   -.1081891
                   |
c.year#c.lnemp1940 |   .1193447   .0631091     1.89   0.059    -.0044234    .2431128
                   |
c.year#c.lnmfg1940 |   .0431104   .0146848     2.94   0.003     .0143109    .0719099
                   |
c.year#c.railroads |   .0003714    .000094     3.95   0.000     .0001871    .0005556
                   |
 c.year#c.inst1944 |   .0579065   .0174458     3.32   0.001     .0236922    .0921209
                   |
   cap30mile_hydro |    -.51584   .2578197    -2.00   0.046     -1.02147   -.0102101
cap30milecapdop10l |    .105256   .0560943     1.88   0.061    -.0047549    .2152668
cap30milecapdop10m |  -.0503939   .0369029    -1.37   0.172     -.122767    .0219791
             _cons |   562.9375   369.1088     1.53   0.127    -160.9499    1286.825
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------+
 Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------+---------------------------------------|
 county_fips |      1959        1959           0    *|
        year |         3           0           3     |
-----------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30milecapdop10l cap30milecapdop10m) nocons /*
> */ ctitle(T5_PC_c8) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***TABLE 6
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. global Geot1 c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econt1 c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. global Econnlnt1 c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. ****************************************
. ***PANEL A
. ****************************************
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treat60post treat60postsulf /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      20.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6788
                                                  Adj R-squared   =     0.6788
                                                  Within R-sq.    =     0.0371
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7723

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0003947   .0004871    -0.81   0.418    -.0013499    .0005606
                    |
          ccapacity |   .0003371   .0002495     1.35   0.177    -.0001522    .0008265
                    |
      c.year#c.laty |   .0726758    .012008     6.05   0.000     .0491261    .0962254
                    |
      c.year#c.lony |   .0457677   .0088491     5.17   0.000     .0284132    .0631222
                    |
              yprcp |   .0003966   .0003119     1.27   0.204    -.0002151    .0010084
               ytav |   .2926135   .1777656     1.65   0.100    -.0560151    .6412422
             ydda29 |  -.0025092   .0027289    -0.92   0.358     -.007861    .0028425
             yddb10 |   .0001814   .0007464     0.24   0.808    -.0012824    .0016453
                    |
 c.year#c.lnpop1940 |  -.5663585   .1443428    -3.92   0.000    -.8494393   -.2832777
                    |
 c.year#c.lnemp1940 |   .6904714   .1426985     4.84   0.000     .4106155    .9703273
                    |
 c.year#c.lnmfg1940 |  -.0342681   .0234741    -1.46   0.144    -.0803049    .0117687
                    |
 c.year#c.railroads |  -.0002149   .0001765    -1.22   0.223     -.000561    .0001312
                    |
  c.year#c.inst1944 |   .0251909    .029661     0.85   0.396    -.0329794    .0833612
                    |
 c.year#c.light1940 |  -.8975719   .1471992    -6.10   0.000    -1.186255   -.6088892
                    |
    cap30mile_hydro |   .0052294   .0531302     0.10   0.922     -.098968    .1094268
               post |  -.2468526   .1398704    -1.76   0.078    -.5211622     .027457
        treat60post |  -.4984836   .2358447    -2.11   0.035    -.9610152    -.035952
    treat60postsulf |   .4409777   .1070441     4.12   0.000      .231046    .6509094
              _cons |   2692.371   1684.249     1.60   0.110    -610.7266    5995.469
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treat60post treat60postsulf) nocons /*
> */ ctitle(T6_PA) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. 
. ****************************************
. ***PANEL B
. ****************************************
. sum sulf if treat60post==1 [fw=births_rs], detail

        Sulfates (in 1000s ug/m-3) based on our coal
                   consumption & AP3 model
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .0457082       .0181232
 5%     .1134279       .0200577
10%     .2511544       .0201102       Obs          56,403,408
25%     .6640919       .0202449       Sum of Wgt.  56,403,408

50%     1.350241                      Mean           1.808394
                        Largest       Std. Dev.      1.487211
75%     2.789671       42.22681
90%     4.205767       46.53744       Variance       2.211796
95%     4.594273       88.90332       Skewness       3.719853
99%     5.009408       102.0495       Kurtosis       174.7856

. *                            sulf
. *-------------------------------------------------------------
. *      Percentiles      Smallest
. * 1%     .0457082       .0181232
. * 5%     .1134279       .0200577
. *10%     .2511544       .0201102       Obs          56,403,408
. *25%     .6640919       .0202449       Sum of Wgt.  56,403,408
. *
. *50%     1.350241                      Mean           1.808394
. *                        Largest       Std. Dev.      1.487211
. *75%     2.789671       42.22681
. *90%     4.205767       46.53744       Variance       2.211796
. *95%     4.594273       88.90332       Skewness       3.719853
. *99%     5.009408       102.0495       Kurtosis       174.7856
. 
. local rmean_sulf = r(mean)

. 
. sum births_rs if treat60post==1, detail

           Number of births by county of residence
-------------------------------------------------------------
      Percentiles      Smallest
 1%           92             30
 5%          148             32
10%          196             36       Obs              29,923
25%          324             36       Sum of Wgt.      29,923

50%          582                      Mean           1884.952
                        Largest       Std. Dev.      5464.554
75%         1319         126482
90%         3838         127338       Variance       2.99e+07
95%         7676         127338       Skewness       12.21611
99%        21798         127338       Kurtosis       230.7106

. *                          births_rs
. *-------------------------------------------------------------
. *      Percentiles      Smallest
. * 1%           92             30
. * 5%          148             32
. *10%          196             36       Obs              29,923
. *25%          324             36       Sum of Wgt.      29,923
. *
. *50%          582                      Mean           1884.952
. *                        Largest       Std. Dev.      5464.554
. *75%         1319         126482
. *90%         3838         127338       Variance       2.99e+07
. *95%         7676         127338       Skewness       12.21611
. *99%        21798         127338       Kurtosis       230.7106
. 
. local births_mean = r(mean)

. local births_county_year_obs = r(N)

. 
. sum ccapacity if treat60post==1 [fw=births_rs]

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
   ccapacity | 56,403,408    263.8316    225.8511          4       1600

. *    Variable |        Obs        Mean    Std. Dev.       Min        Max
. *-------------+---------------------------------------------------------
. *   ccapacity | 56,403,408    263.8316    225.8511          4       1600
. local cap_mean = r(mean)

. 
. sum ccapacity if treat60post==1

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
   ccapacity |     29,923    191.7185    231.8447          4       1600

. *    Variable |        Obs        Mean    Std. Dev.       Min        Max
. *-------------+---------------------------------------------------------
. *   ccapacity |     29,923    191.7185    231.8447          4       1600
. local cap_obs = r(N)

. 
. sum generation if treat60post==1 [fw=births_rs]

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
  generation | 49,211,842    1599.874    1438.076          0    11768.5

. *    Variable |        Obs        Mean    Std. Dev.       Min        Max
. *-------------+---------------------------------------------------------
. *  generation | 49,211,842    1599.874    1438.076          0    11768.5
. local gen_mean = r(mean)

. 
. sum generation if treat60post==1

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
  generation |     25,881    1176.903    1640.595          0    11768.5

. *    Variable |        Obs        Mean    Std. Dev.       Min        Max
. *-------------+---------------------------------------------------------
. *  generation |     25,881    1176.903    1640.595          0    11768.5
. local gen_obs = r(N)

. 
. 
. merge m:1 county_fips using data/dist_newhydro_after1962.dta,

    Result                           # of obs.
    -----------------------------------------
    not matched                         1,250
        from master                         0  (_merge==1)
        from using                      1,250  (_merge==2)

    matched                           132,000  (_merge==3)
    -----------------------------------------

. keep if _merge==3
(1,250 observations deleted)

. drop _merge

. 
. bysort plant_id treat: egen mindist_coal = min(dist_miles)

. replace mindist_coal =. if treat==0
(105,600 real changes made, 105,600 to missing)

. replace mindist_coal = (dist_miles == mindist_coal)
(132,000 real changes made)

. replace mindist_coal =. if treat==0
(105,600 real changes made, 105,600 to missing)

. 
. gen ddist_newhydro_aux = dist_newhydro - dist_miles if mindist_coal==1
(125,250 missing values generated)

. bysort plant_id treat: egen ddist_newhydro = mean(ddist_newhydro_aux)
(105600 missing values generated)

. replace ddist_newhydro =. if treat==0
(0 real changes made)

. 
. sort plant_id county_fips year

. order idcountyplant-dist_miles mindist_coal dist_newhydro ddist_newhydro treat

. 
. sum ddist_newhydro [fw=births_rs], detail

                       ddist_newhydro
-------------------------------------------------------------
      Percentiles      Smallest
 1%    -16.26138      -16.26138
 5%     17.52102      -16.26138
10%     40.78881      -16.26138       Obs          78,767,856
25%     77.43867      -16.26138       Sum of Wgt.  78,767,856

50%     153.3406                      Mean           173.7153
                        Largest       Std. Dev.      108.8488
75%     252.9309       610.2101
90%     321.7703       610.2101       Variance       11848.06
95%     369.6405       610.2101       Skewness       .4713779
99%     434.8539       610.2101       Kurtosis       2.579424

. *                       ddist_newhydro
. *-------------------------------------------------------------
. *      Percentiles      Smallest
. * 1%    -16.26138      -16.26138
. * 5%     17.52102      -16.26138
. *10%     40.78881      -16.26138       Obs          78,767,856
. *25%     77.43867      -16.26138       Sum of Wgt.  78,767,856
. *
. *50%     153.3406                      Mean           173.7153
. *                        Largest       Std. Dev.      108.8488
. *75%     252.9309       610.2101
. *90%     321.7703       610.2101       Variance       11848.06
. *95%     369.6405       610.2101       Skewness       .4713779
. *99%     434.8539       610.2101       Kurtosis       2.579424
. *250 miles is approximately the 75pctile, which is what hydro would 
. *make up for coal if we includes pumped storage
. 
. bysort plant_id treat: gen nplant = _n

. replace nplant =. if treat==0
(105,600 real changes made, 105,600 to missing)

. sum ddist_newhydro if ddist_newhydro<=250 & nplant==1 [fw=births_rs], detail

                       ddist_newhydro
-------------------------------------------------------------
      Percentiles      Smallest
 1%    -16.26138      -16.26138
 5%     16.21825      -12.23246
10%     38.38426       8.161737       Obs             609,151
25%     74.34941       12.77319       Sum of Wgt.     609,151

50%     140.3244                      Mean           132.5935
                        Largest       Std. Dev.      70.28884
75%     199.2112       241.7923
90%     220.9445        244.806       Variance       4940.521
95%     241.7923       246.8701       Skewness      -.2093427
99%     241.7923       247.1189       Kurtosis       1.953838

. *                       ddist_newhydro
. *-------------------------------------------------------------
. *      Percentiles      Smallest
. * 1%    -16.26138      -16.26138
. * 5%     17.34225      -12.23246
. *10%     38.38426       8.161737       Obs             624,219
. *25%     76.41632       12.77319       Sum of Wgt.     624,219
. *
. *50%      129.483                      Mean           127.1616
. *                        Largest       Std. Dev.      64.53809
. *75%     185.7573       241.7923
. *90%      207.209        244.806       Variance       4165.165
. *95%     212.1309       246.8701       Skewness      -.3473706
. *99%     237.9106       247.1189       Kurtosis       2.162483
. 
. local rmean_tlines_hydro = r(mean)

. 
. sum ddist_newhydro if ddist_newhydro<=250 & nplant==1

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
ddist_newh~o |        194    125.5211    68.88271  -16.26138   247.1189

. *    Variable |        Obs        Mean    Std. Dev.       Min        Max
. *-------------+---------------------------------------------------------
. *ddist_newh~o |        194    125.5211    68.88271  -16.26138   247.1189
. local tlines_county_obs_hydro = r(N)

. 
. sum generation if treat60post==1 & ddist_newhydro<=250 [fw=births_rs]

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
  generation | 25,760,885    1578.082    1252.657          0    11768.5

. *    Variable |        Obs        Mean    Std. Dev.       Min        Max
. *-------------+---------------------------------------------------------
. *  generation | 25,760,885    1578.082    1252.657          0    11768.5
. local gen_mean_hydro = r(mean)

. 
. sum generation if treat60post==1 & ddist_newhydro<=250

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
  generation |      7,633    1365.331    1643.815          0    11768.5

. *    Variable |        Obs        Mean    Std. Dev.       Min        Max
. *-------------+---------------------------------------------------------
. *  generation |      7,633    1365.331    1643.815          0    11768.5
. local gen_obs_hydro = r(N)

. 
. di (`gen_mean_hydro' * `gen_obs_hydro' * 0.01 * (0.041*2.5))/25
493.86543

. *$493.86543 million (1990 USD) (transmission losses)
. local cost_tlines_newhydro = [(`rmean_tlines_hydro' * `tlines_county_obs_hydro' * 0.32464194)/40] /*
> */ + [(`gen_mean_hydro' * `gen_obs_hydro' * 0.01 * (0.041*2.5))/25]

. di `cost_tlines_newhydro'
702.63569

. *$694.86588 million (1990 USD)
. *maximum transmission voltages in the United States in 1954: 345 kv (FPC_1964_The 1964 national power survey, p.14)
. *representative investment per mile of 345 kv transmission line, including right-of-way: 
. *$77,000 (FPC_1964_The 1964 national power survey, p.151, 1964 USD) -- $324,641.94 (1990 USD) or $0.32464194 million
. *electricity prices 1960: $0.018cents (2005 USD, https://www.eia.gov/totalenergy/data/annual/showtext.php?t=ptb0810) --
>  $0.01 (1990 USD)
. *transmission losses per 100 miles (4.1 percent)
. 
. sum sulf if treat60post==1 & ddist_newhydro<=250 [fw=births_rs], detail

        Sulfates (in 1000s ug/m-3) based on our coal
                   consumption & AP3 model
-------------------------------------------------------------
      Percentiles      Smallest
 1%     .0417178       .0222887
 5%     .0986279       .0230734
10%     .2742158        .023752       Obs          29,422,841
25%      .774837       .0246564       Sum of Wgt.  29,422,841

50%     1.607908                      Mean           1.994829
                        Largest       Std. Dev.      1.550381
75%      3.23378       42.22681
90%     4.227764       46.53744       Variance       2.403682
95%     4.596657       88.90332       Skewness       5.520001
99%     5.109356       102.0495       Kurtosis       279.4501

. *                            sulf
. *-------------------------------------------------------------
. *      Percentiles      Smallest
. * 1%      .043188       .0246564
. * 5%      .228789       .0262609
. *10%     .3123894       .0289283       Obs          23,813,851
. *25%     .7936416       .0289283       Sum of Wgt.  23,813,851
. *
. *50%     1.655592                      Mean           2.093757
. *                        Largest       Std. Dev.      1.571961
. *75%     3.371047        5.50089
. *90%     4.317475       9.530711       Variance        2.47106
. *95%     4.829809       88.90332       Skewness       5.543063
. *99%     5.109356       102.0495       Kurtosis       302.3458
. 
. local rmean_sulf_hydro = r(mean)

. 
. sum births_rs if treat60post==1 & ddist_newhydro<=250, detail

           Number of births by county of residence
-------------------------------------------------------------
      Percentiles      Smallest
 1%          110             30
 5%          174             38
10%          230             40       Obs               8,790
25%          412             40       Sum of Wgt.       8,790

50%          910                      Mean           3347.308
                        Largest       Std. Dev.      6162.076
75%         3074          46586
90%         9880          46586       Variance       3.80e+07
95%        15726          46586       Skewness       3.559478
99%        33106          47915       Kurtosis        18.5489

. *                          births_rs
. *-------------------------------------------------------------
. *      Percentiles      Smallest
. * 1%          112             40
. * 5%          176             42
. *10%          240             54       Obs               7,031
. *25%          410             56       Sum of Wgt.       7,031
. *
. *50%          890                      Mean           3386.979
. *                        Largest       Std. Dev.       6101.59
. *75%         3394          46586
. *90%        10164          46586       Variance       3.72e+07
. *95%        15576          46586       Skewness       3.558306
. *99%        26388          47915       Kurtosis       19.37691
. 
. local births_mean_hydro = r(mean)

. local births_county_year_obs_hydro = r(N)

. 
. ****************************************
. ***PANEL B
. ****************************************
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treat60post treat60postsulf /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips)
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      20.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6788
                                                  Adj R-squared   =     0.6788
                                                  Within R-sq.    =     0.0371
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7723

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0003947   .0004871    -0.81   0.418    -.0013499    .0005606
                    |
          ccapacity |   .0003371   .0002495     1.35   0.177    -.0001522    .0008265
                    |
      c.year#c.laty |   .0726758    .012008     6.05   0.000     .0491261    .0962254
                    |
      c.year#c.lony |   .0457677   .0088491     5.17   0.000     .0284132    .0631222
                    |
              yprcp |   .0003966   .0003119     1.27   0.204    -.0002151    .0010084
               ytav |   .2926135   .1777656     1.65   0.100    -.0560151    .6412422
             ydda29 |  -.0025092   .0027289    -0.92   0.358     -.007861    .0028425
             yddb10 |   .0001814   .0007464     0.24   0.808    -.0012824    .0016453
                    |
 c.year#c.lnpop1940 |  -.5663585   .1443428    -3.92   0.000    -.8494393   -.2832777
                    |
 c.year#c.lnemp1940 |   .6904714   .1426985     4.84   0.000     .4106155    .9703273
                    |
 c.year#c.lnmfg1940 |  -.0342681   .0234741    -1.46   0.144    -.0803049    .0117687
                    |
 c.year#c.railroads |  -.0002149   .0001765    -1.22   0.223     -.000561    .0001312
                    |
  c.year#c.inst1944 |   .0251909    .029661     0.85   0.396    -.0329794    .0833612
                    |
 c.year#c.light1940 |  -.8975719   .1471992    -6.10   0.000    -1.186255   -.6088892
                    |
    cap30mile_hydro |   .0052294   .0531302     0.10   0.922     -.098968    .1094268
               post |  -.2468526   .1398704    -1.76   0.078    -.5211622     .027457
        treat60post |  -.4984836   .2358447    -2.11   0.035    -.9610152    -.035952
    treat60postsulf |   .4409777   .1070441     4.12   0.000      .231046    .6509094
              _cons |   2692.371   1684.249     1.60   0.110    -610.7266    5995.469
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. local sulfred_stack = 95

. local sulfred_newhydro = 100

. local sulfred_bag = 99

. local affplt_stack = 270

. local affplt_newhydro = 194

. local affplt_bag = 270

. local cnterf_stack = [(_b[treat60postsulf] * `rmean_sulf' *0.95) * ((`births_mean' * `births_county_year_obs') /1000)] 
> /25

. local cnterf_newhydro = [(_b[treat60postsulf] * `rmean_sulf_hydro') * ((`births_mean_hydro' * `births_county_year_obs_h
> ydro') /1000)] /25

. local cnterf_bag = [(_b[treat60postsulf] * `rmean_sulf' *0.99) * ((`births_mean' * `births_county_year_obs') /1000)] /2
> 5

. local costplife_stack = [2.73 * [(`cap_mean' * 1000 * `cap_obs' * 10)/(40 * 25) + (`gen_mean' * 1000000 * `gen_obs' * 0
> .00015)/25]] / `cnterf_stack'

. local costplife_newhydro = (`cost_tlines_newhydro'*1000000) / `cnterf_newhydro'

. local costplife_baglbound = [(270 * 110000) + (270 * 165000 * 3.70)] / `cnterf_bag'

. local costplife_bagubound = [(270 * 750000) + (270 * 198000 * 3.70)] / `cnterf_bag'

. *1 dollar in 1974 is equivalent to 2.73 dollars in 1990
. *capacity is measured in megawatts -- 1 megawatt = 1000 kilowatts
. *generation is measured in millions of kilowatt-hours
. *1 mill = 0.001 dollar -- a mill is equal to 1/1,000 of a U.S. dollar, or 1/10 of one cent 
. *There were two primary costs associated with baghouses: installation costs and fly ash disposal. 
. *For a typical large power plant the installation costs, annualized over the expected 15-year lifespan, 
. *could range from $110,000 to $750,000 (1990 USD) per year depending on the desired airflow (USHEW, 1969). 
. *The cost of fly ash disposal for electric utilities was $3.70 per ton, and the typical power plant in 
. *the sample produced between 165,000 and 198,000 tons of fly ash per year. Thus the annual cost of pollution 
. *abatement ranged from $720,000 to $1.48 million per plant.
. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treat60post treat60postsulf) nocons /*
> */ ctitle(T6_PB) se bdec(3) sdec(3) rdec(3) addstat("sulfred_stack", `sulfred_stack', "affplt_stack", `affplt_stack', /
> *
> */ "cnterf_stack", `cnterf_stack', "costplife_stack", `costplife_stack', "sulfred_newhydro", `sulfred_newhydro', "affpl
> t_newhydro", /*
> */ `affplt_newhydro', "cnterf_newhydro", `cnterf_newhydro', "costplife_newhydro", `costplife_newhydro', "sulfred_bag", 
> `sulfred_bag', /*
> */ "affplt_bag", `affplt_bag', "cnterf_bag", `cnterf_bag', "costplife_baglbound", `costplife_baglbound', "costplife_bag
> ubound", /*
> */ `costplife_bagubound') excel append
logfiles/Canary_output.xml
dir : seeout

. *As explained in Appendix B.3.3, we approximate the number of infant lives saved and cost per life saved, and take the 
> midpoint from 
. *the cost per life saved between a lower bound and an upper bound for the counterfactual for baghouses.
. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX TABLE A.1
. ********************************************************************************
. ********************************************************************************
. *compilation of information from previous studies cited there
. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX TABLE A.2
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/tspEPA_1957_62_semibalanced.dta, clear

. *semi-balanced: at least 4 out of 6 obs (or at least two thirds of the obs)
. *these annual summary data on pollution were provided by EPA through a FOIA request
. 
. global Geo c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econ c.year#c.emp1940 c.year#c.mfg1940

. 
. reg tsp i.state_fips#i.year /*
> */ $Geo /*
> */ cap30mile /*
> */ , cluster(county_fips) 
note: 1b.state_fips#1958.year identifies no observations in the sample
note: 4.state_fips#1958.year identifies no observations in the sample
note: 10.state_fips#1958.year identifies no observations in the sample
note: 10.state_fips#1959.year identifies no observations in the sample
note: 11.state_fips#1957b.year identifies no observations in the sample
note: 13.state_fips#1958.year identifies no observations in the sample
note: 17.state_fips#1957b.year identifies no observations in the sample
note: 17.state_fips#1959.year identifies no observations in the sample
note: 20.state_fips#1958.year identifies no observations in the sample
note: 23.state_fips#1957b.year identifies no observations in the sample
note: 26.state_fips#1958.year identifies no observations in the sample
note: 28.state_fips#1961.year identifies no observations in the sample
note: 32.state_fips#1957b.year identifies no observations in the sample
note: 32.state_fips#1958.year identifies no observations in the sample
note: 33.state_fips#1957b.year identifies no observations in the sample
note: 33.state_fips#1958.year identifies no observations in the sample
note: 34.state_fips#1957b.year identifies no observations in the sample
note: 36.state_fips#1958.year identifies no observations in the sample
note: 37.state_fips#1962.year identifies no observations in the sample
note: 49.state_fips#1957b.year identifies no observations in the sample

Linear regression                               Number of obs     =        433
                                                F(48, 84)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7234
                                                Root MSE          =      40.53

                              (Std. Err. adjusted for 85 clusters in county_fips)
---------------------------------------------------------------------------------
                |               Robust
            tsp |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
state_fips#year |
        1 1958  |          0  (empty)
        1 1959  |   9.787808   8.443873     1.16   0.250    -7.003759    26.57938
        1 1960  |  -19.51279   19.49922    -1.00   0.320    -58.28913    19.26354
        1 1961  |   28.43877   18.17414     1.56   0.121    -7.702505    64.58004
        1 1962  |  -24.80462   16.54254    -1.50   0.138    -57.70127    8.092043
        4 1957  |   6.402325   151.5271     0.04   0.966     -294.926    307.7306
        4 1958  |          0  (empty)
        4 1959  |  -15.79663   155.5998    -0.10   0.919    -325.2239    293.6306
        4 1960  |  -105.4014   157.8074    -0.67   0.506    -419.2188     208.416
        4 1961  |  -91.47284   154.3743    -0.59   0.555     -398.463    215.5174
        4 1962  |  -102.2023   154.6171    -0.66   0.510    -409.6753    205.2706
        5 1957  |   4.769115   29.66828     0.16   0.873    -54.22951    63.76774
        5 1958  |  -34.40372   30.44782    -1.13   0.262    -94.95254     26.1451
        5 1959  |  -50.33036   31.94972    -1.58   0.119    -113.8659    13.20516
        5 1960  |  -70.87646    37.0094    -1.92   0.059    -144.4737    2.720794
        5 1961  |  -56.09583   29.31884    -1.91   0.059    -114.3996      2.2079
        5 1962  |  -82.26237   39.23577    -2.10   0.039     -160.287    -4.23774
        6 1957  |   69.15736   149.7425     0.46   0.645     -228.622    366.9368
        6 1958  |   52.22043   150.8779     0.35   0.730    -247.8169    352.2577
        6 1959  |   35.45886   154.5256     0.23   0.819    -271.8322    342.7499
        6 1960  |   16.88638    155.403     0.11   0.914    -292.1494    325.9222
        6 1961  |  -4.227246   156.3572    -0.03   0.978    -315.1607    306.7062
        6 1962  |   21.12793   154.7615     0.14   0.892    -286.6323    328.8882
        8 1957  |   34.09474   97.22566     0.35   0.727    -159.2491    227.4386
        8 1958  |  -8.280645   99.17879    -0.08   0.934    -205.5086    188.9473
        8 1959  |   22.23862   101.1889     0.22   0.827    -178.9865    223.4638
        8 1960  |  -4.243724   107.7205    -0.04   0.969    -218.4578    209.9704
        8 1961  |   2.488223   102.0789     0.02   0.981    -200.5069    205.4833
        8 1962  |  -51.73704   109.6169    -0.47   0.638    -269.7222    166.2481
        9 1957  |  -110.6064   91.78157    -1.21   0.232    -293.1241    71.91131
        9 1958  |  -103.6925    88.9404    -1.17   0.247    -280.5602    73.17527
        9 1959  |  -116.3947   85.69439    -1.36   0.178    -286.8074    54.01799
        9 1960  |  -106.7686    89.6891    -1.19   0.237    -285.1252    71.58796
        9 1961  |  -139.6533   87.00546    -1.61   0.112    -312.6732    33.36659
        9 1962  |  -124.2263   94.01551    -1.32   0.190    -311.1865    62.73383
       10 1957  |  -24.54722   72.00394    -0.34   0.734     -167.735    118.6405
       10 1958  |          0  (empty)
       10 1959  |          0  (empty)
       10 1960  |   .4705363   67.38778     0.01   0.994    -133.5375    134.4785
       10 1961  |  -35.64704   69.59038    -0.51   0.610    -174.0351    102.7411
       10 1962  |  -89.45559   73.54373    -1.22   0.227    -235.7054    56.79418
       11 1957  |          0  (empty)
       11 1958  |  -93.18441   59.39512    -1.57   0.120    -211.2981    24.92931
       11 1959  |  -124.0847   62.64189    -1.98   0.051     -248.655    .4855803
       11 1960  |  -88.60253   60.99071    -1.45   0.150    -209.8893     32.6842
       11 1961  |  -90.96477   59.98829    -1.52   0.133    -210.2581    28.32853
       11 1962  |   -142.284   63.26687    -2.25   0.027    -268.0971   -16.47089
       12 1957  |   -91.0983    56.0002    -1.63   0.108    -202.4608    20.26425
       12 1958  |  -94.66258   47.78646    -1.98   0.051    -189.6912    .3660258
       12 1959  |  -48.75862   59.92423    -0.81   0.418    -167.9245    70.40729
       12 1960  |  -81.93117   50.16229    -1.63   0.106    -181.6844    17.82204
       12 1961  |  -153.5528   59.65866    -2.57   0.012    -272.1906   -34.91498
       12 1962  |  -138.4612   52.22315    -2.65   0.010    -242.3127   -34.60974
       13 1957  |  -41.51641   15.74525    -2.64   0.010    -72.82758   -10.20525
       13 1958  |          0  (empty)
       13 1959  |  -30.49569   18.25066    -1.67   0.098    -66.78912    5.797738
       13 1960  |  -45.51909   24.22844    -1.88   0.064    -93.69999    2.661813
       13 1961  |  -28.56054   22.76537    -1.25   0.213    -73.83197     16.7109
       13 1962  |  -59.74004   17.72705    -3.37   0.001    -94.99222   -24.48786
       17 1957  |          0  (empty)
       17 1958  |  -75.80504    77.7948    -0.97   0.333    -230.5085    78.89845
       17 1959  |          0  (empty)
       17 1960  |   -109.064   87.64936    -1.24   0.217    -283.3644    65.23635
       17 1961  |  -75.38939   77.98691    -0.97   0.336    -230.4749    79.69614
       17 1962  |   -190.503   96.38398    -1.98   0.051    -382.1732    1.167074
       18 1957  |    62.9059   60.30924     1.04   0.300    -57.02565    182.8374
       18 1958  |  -6.225976   85.89435    -0.07   0.942    -177.0363    164.5844
       18 1959  |  -10.69964   54.83562    -0.20   0.846    -119.7463    98.34701
       18 1960  |  -59.31615   73.40929    -0.81   0.421    -205.2986    86.66627
       18 1961  |  -65.53245    64.1725    -1.02   0.310    -193.1465    62.08159
       18 1962  |  -67.81171   65.87195    -1.03   0.306    -198.8053    63.18188
       19 1957  |  -2.780192   67.47814    -0.04   0.967    -136.9679    131.4075
       19 1958  |   -8.15859   68.46771    -0.12   0.905    -144.3141     127.997
       19 1959  |  -38.26451   87.08993    -0.44   0.662    -211.4524    134.9234
       19 1960  |  -60.06134   105.8242    -0.57   0.572    -270.5044    150.3817
       19 1961  |  -55.75567   71.27446    -0.78   0.436    -197.4928    85.98142
       19 1962  |  -91.55643     83.689    -1.09   0.277    -257.9812    74.86832
       20 1957  |  -34.46079   58.88704    -0.59   0.560    -151.5641    82.64255
       20 1958  |          0  (empty)
       20 1959  |  -44.41625   60.27119    -0.74   0.463    -164.2721    75.43963
       20 1960  |  -47.21549   68.70566    -0.69   0.494    -183.8442    89.41324
       20 1961  |  -46.80815   60.33691    -0.78   0.440    -166.7947    73.17841
       20 1962  |  -72.14067   68.73746    -1.05   0.297    -208.8327     64.5513
       23 1957  |          0  (empty)
       23 1958  |  -78.82224   107.9711    -0.73   0.467    -293.5346    135.8901
       23 1959  |  -141.4388   112.5965    -1.26   0.213    -365.3492    82.47164
       23 1960  |  -145.2198   116.3739    -1.25   0.216    -376.6422    86.20252
       23 1961  |  -154.9473   112.3367    -1.38   0.171    -378.3412    68.44652
       23 1962  |  -146.1306   117.4815    -1.24   0.217    -379.7554    87.49425
       24 1957  |  -66.80632    65.3359    -1.02   0.309    -196.7339    63.12128
       24 1958  |  -68.37229    61.6732    -1.11   0.271    -191.0162    54.27163
       24 1959  |  -112.5981   79.12503    -1.42   0.158    -269.9469    44.75071
       24 1960  |  -99.16649      73.03    -1.36   0.178    -244.3947    46.06168
       24 1961  |  -109.6835   74.02081    -1.48   0.142     -256.882    37.51498
       24 1962  |   -122.237   68.23437    -1.79   0.077    -257.9286    13.45448
       25 1957  |  -138.5398   102.8504    -1.35   0.182    -343.0691    65.98956
       25 1958  |  -99.71874   99.36661    -1.00   0.318    -297.3201    97.88266
       25 1959  |  -115.7052   96.04014    -1.20   0.232    -306.6916    75.28115
       25 1960  |  -134.3329   98.45949    -1.36   0.176    -330.1304     61.4646
       25 1961  |  -141.3506   94.49323    -1.50   0.138    -329.2607     46.5596
       25 1962  |  -132.4523   97.60331    -1.36   0.178    -326.5471    61.64261
       26 1957  |  -72.69943   63.74399    -1.14   0.257    -199.4614    54.06249
       26 1958  |          0  (empty)
       26 1959  |  -98.54399   67.73984    -1.45   0.149    -233.2521    36.16412
       26 1960  |  -116.0846      74.65    -1.56   0.124    -264.5343    32.36506
       26 1961  |  -108.6912   64.94138    -1.67   0.098    -237.8343    20.45184
       26 1962  |  -147.1442   75.30118    -1.95   0.054    -296.8889    2.600469
       27 1957  |   -42.8872   83.90269    -0.51   0.611    -209.7369    123.9625
       27 1958  |  -75.16504   83.51089    -0.90   0.371    -241.2356    90.90552
       27 1959  |  -78.29027   86.98493    -0.90   0.371    -251.2694    94.68881
       27 1960  |  -112.7171   93.14737    -1.21   0.230    -297.9508    72.51669
       27 1961  |  -117.1807   87.25183    -1.34   0.183    -290.6905    56.32915
       27 1962  |   -109.181   93.32024    -1.17   0.245    -294.7586    76.39651
       28 1957  |  -70.54309   29.85143    -2.36   0.020    -129.9059   -11.18024
       28 1958  |  -36.97671   27.36177    -1.35   0.180    -91.38859    17.43516
       28 1959  |  -58.42603   28.40205    -2.06   0.043    -114.9066   -1.945436
       28 1960  |  -77.94712   31.97915    -2.44   0.017    -141.5412   -14.35307
       28 1961  |          0  (empty)
       28 1962  |  -108.5841   41.04071    -2.65   0.010     -190.198   -26.97014
       29 1957  |   17.96069    42.0613     0.43   0.670    -65.68281    101.6042
       29 1958  |   10.79695    54.3632     0.20   0.843    -97.31023    118.9041
       29 1959  |  -7.121135   53.89672    -0.13   0.895    -114.3007    100.0584
       29 1960  |  -44.49888   61.77089    -0.72   0.473    -167.3371    78.33932
       29 1961  |  -20.68152   47.22296    -0.44   0.663    -114.5896    73.22651
       29 1962  |  -58.63792   56.35198    -1.04   0.301       -170.7    53.42417
       31 1957  |   -31.8828   68.92811    -0.46   0.645    -168.9539    105.1883
       31 1958  |  -87.07555    86.9514    -1.00   0.319     -259.988    85.83685
       31 1959  |  -50.12273   113.6272    -0.44   0.660    -276.0828    175.8373
       31 1960  |  -97.93142   96.65971    -1.01   0.314    -290.1498      94.287
       31 1961  |  -94.91422   86.87529    -1.09   0.278    -267.6753    77.84682
       31 1962  |  -87.46488     83.261    -1.05   0.297    -253.0385    78.10875
       32 1957  |          0  (empty)
       32 1958  |          0  (empty)
       32 1959  |  -93.10887   148.1065    -0.63   0.531    -387.6348    201.4171
       32 1960  |  -95.11754   152.3908    -0.62   0.534    -398.1633    207.9282
       32 1961  |  -97.64226   151.4959    -0.64   0.521    -398.9084    203.6239
       32 1962  |  -89.37027   150.1058    -0.60   0.553    -387.8721    209.1316
       33 1957  |          0  (empty)
       33 1958  |          0  (empty)
       33 1959  |  -198.3595   109.4028    -1.81   0.073    -415.9189    19.19984
       33 1960  |  -203.0779   111.3876    -1.82   0.072    -424.5843    18.42859
       33 1961  |  -214.3393   110.1771    -1.95   0.055    -433.4385    4.759824
       33 1962  |  -193.2188   112.6104    -1.72   0.090    -417.1569    30.71926
       34 1957  |          0  (empty)
       34 1958  |  -213.7017   90.60261    -2.36   0.021    -393.8749   -33.52846
       34 1959  |  -210.0325   88.94289    -2.36   0.021    -386.9052   -33.15979
       34 1960  |  -234.3563   93.17703    -2.52   0.014    -419.6491   -49.06357
       34 1961  |  -261.2737    101.013    -2.59   0.011    -462.1491   -60.39837
       34 1962  |  -296.9532    108.542    -2.74   0.008    -512.8008   -81.10564
       35 1957  |   87.90001   115.9798     0.76   0.451    -142.7385    318.5386
       35 1958  |    56.5496   116.5552     0.49   0.629    -175.2331    288.3323
       35 1959  |   112.7903   121.0703     0.93   0.354    -127.9712    353.5518
       35 1960  |   105.9858   126.2081     0.84   0.403    -144.9929    356.9645
       35 1961  |   51.52312   125.5305     0.41   0.683    -198.1079    301.1542
       35 1962  |   31.39536   120.6129     0.26   0.795    -208.4565    271.2472
       36 1957  |   -96.6589   85.33936    -1.13   0.261    -266.3656    73.04778
       36 1958  |          0  (empty)
       36 1959  |  -95.50609   81.56785    -1.17   0.245    -257.7127    66.70052
       36 1960  |  -113.0475   83.56759    -1.35   0.180    -279.2308    53.13585
       36 1961  |  -118.5631   83.79051    -1.41   0.161    -285.1897    48.06353
       36 1962  |  -113.2457   84.55606    -1.34   0.184    -281.3947    54.90335
       37 1957  |  -61.37092   35.84043    -1.71   0.091    -132.6435    9.901708
       37 1958  |  -79.64446   36.19884    -2.20   0.031    -151.6298   -7.659093
       37 1959  |    -52.137   31.53316    -1.65   0.102    -114.8441    10.57015
       37 1960  |  -86.10394   34.71445    -2.48   0.015    -155.1374   -17.07045
       37 1961  |  -58.85741   36.66883    -1.61   0.112    -131.7774    14.06258
       37 1962  |          0  (empty)
       38 1957  |  -76.91182   114.5415    -0.67   0.504    -304.6902    150.8666
       38 1958  |  -128.4113   120.3811    -1.07   0.289    -367.8024    110.9797
       38 1959  |  -136.0252   124.4203    -1.09   0.277    -383.4487    111.3983
       38 1960  |   -115.135   125.6343    -0.92   0.362    -364.9724    134.7025
       38 1961  |  -135.7853   122.3238    -1.11   0.270    -379.0395     107.469
       38 1962  |  -105.2887   115.8011    -0.91   0.366    -335.5719    124.9946
       39 1957  |  -31.92756   58.15446    -0.55   0.584    -147.5741    83.71896
       39 1958  |  -53.71036    59.3569    -0.90   0.368    -171.7481    64.32734
       39 1959  |  -47.27598   52.55517    -0.90   0.371    -151.7877    57.23575
       39 1960  |  -76.72777   60.92325    -1.26   0.211    -197.8803     44.4248
       39 1961  |  -74.36984   54.43582    -1.37   0.176    -182.6214    33.88177
       39 1962  |  -93.23135   57.97587    -1.61   0.112    -208.5227    22.06002
       42 1957  |  -56.12057   78.61924    -0.71   0.477    -212.4636    100.2224
       42 1958  |  -99.54776   76.70313    -1.30   0.198    -252.0803    52.98483
       42 1959  |  -52.50777   98.63874    -0.53   0.596    -248.6617    143.6462
       42 1960  |  -113.5097   75.46872    -1.50   0.136    -263.5875    36.56816
       42 1961  |  -122.2189   73.06946    -1.67   0.098    -267.5255    23.08777
       42 1962  |  -129.7774   81.49362    -1.59   0.115    -291.8364    32.28164
       44 1957  |  -117.0198   98.47473    -1.19   0.238    -312.8476    78.80801
       44 1958  |  -69.11416   96.05286    -0.72   0.474    -260.1258    121.8975
       44 1959  |  -129.2553   98.91875    -1.31   0.195    -325.9661    67.45543
       44 1960  |  -128.8357   104.2167    -1.24   0.220     -336.082    78.41069
       44 1961  |  -151.8424   93.74191    -1.62   0.109    -338.2585    34.57368
       44 1962  |  -134.1299   99.85498    -1.34   0.183    -332.7025    64.44266
       45 1957  |   -64.1056   34.45578    -1.86   0.066    -132.6247    4.413508
       45 1958  |  -69.84176   29.70186    -2.35   0.021    -128.9072   -10.77635
       45 1959  |  -110.1544   31.41645    -3.51   0.001    -172.6294   -47.67934
       45 1960  |  -96.46261   28.19565    -3.42   0.001    -152.5328   -40.39248
       45 1961  |  -121.3862   29.61187    -4.10   0.000    -180.2727    -62.4998
       45 1962  |  -110.2648   29.19141    -3.78   0.000    -168.3151   -52.21445
       46 1957  |  -78.15985   85.86588    -0.91   0.365    -248.9136    92.59386
       46 1958  |  -73.40814   90.52012    -0.81   0.420    -253.4173     106.601
       46 1959  |  -79.10583   91.26773    -0.87   0.389    -260.6017    102.3901
       46 1960  |  -67.36626   97.72931    -0.69   0.493    -261.7117    126.9792
       46 1961  |  -111.1356   90.14541    -1.23   0.221    -290.3996    68.12846
       46 1962  |  -73.09358   89.24344    -0.82   0.415     -250.564    104.3768
       47 1957  |    3.69788   12.88117     0.29   0.775    -21.91774     29.3135
       47 1958  |   14.59063   57.59534     0.25   0.801    -99.94401    129.1253
       47 1959  |   31.22766   30.24112     1.03   0.305    -28.91012    91.36545
       47 1960  |  -30.38991   53.41818    -0.57   0.571    -136.6178      75.838
       47 1961  |  -.0003841   59.41205    -0.00   1.000    -118.1478     118.147
       47 1962  |  -16.71674    36.9231    -0.45   0.652    -90.14237    56.70888
       48 1957  |   -31.6389   74.32687    -0.43   0.671     -179.446    116.1682
       48 1958  |  -71.37399   74.83209    -0.95   0.343    -220.1858    77.43783
       48 1959  |  -37.56882    75.7521    -0.50   0.621    -188.2102    113.0726
       48 1960  |  -62.69763    78.6918    -0.80   0.428    -219.1849    93.78965
       48 1961  |  -67.55055     72.763    -0.93   0.356    -212.2478    77.14664
       48 1962  |  -116.6221     74.635    -1.56   0.122     -265.042    31.79775
       49 1957  |          0  (empty)
       49 1958  |  -15.54963   124.9999    -0.12   0.901    -264.1256    233.0264
       49 1959  |   13.30474   124.4095     0.11   0.915    -234.0973    260.7067
       49 1960  |   2.946621    128.735     0.02   0.982     -253.057    258.9502
       49 1961  |   30.17909   128.4365     0.23   0.815     -225.231    285.5892
       49 1962  |   40.49398   127.2455     0.32   0.751    -212.5477    293.5356
       50 1957  |  -173.6931   99.09114    -1.75   0.083    -370.7467    23.36049
       50 1958  |  -173.7647     99.926    -1.74   0.086    -372.4785    24.94916
       50 1959  |  -179.0147   97.04709    -1.84   0.069    -372.0035    13.97405
       50 1960  |  -183.7354   100.6693    -1.83   0.072    -383.9274    16.45655
       50 1961  |  -176.1991   100.1368    -1.76   0.082    -375.3321    22.93377
       50 1962  |  -175.2023   101.7826    -1.72   0.089    -377.6082    27.20356
       51 1957  |  -89.45051   61.10851    -1.46   0.147    -210.9715    32.07046
       51 1958  |  -107.4263   73.37734    -1.46   0.147    -253.3452     38.4926
       51 1959  |  -122.3992   69.31125    -1.77   0.081    -260.2322    15.43384
       51 1960  |  -139.6733   57.95966    -2.41   0.018    -254.9324   -24.41416
       51 1961  |  -127.9015   57.71422    -2.22   0.029    -242.6725   -13.13042
       51 1962  |  -124.2927   62.19618    -2.00   0.049    -247.9766   -.6087493
       54 1957  |    15.1779   45.82686     0.33   0.741    -75.95383    106.3096
       54 1958  |   20.51765   43.85077     0.47   0.641    -66.68442    107.7197
       54 1959  |   41.36568   46.03355     0.90   0.371    -50.17709    132.9085
       54 1960  |   22.81199   47.29599     0.48   0.631    -71.24126    116.8653
       54 1961  |   42.14911   43.60639     0.97   0.337    -44.56698    128.8652
       54 1962  |   42.29419   43.29156     0.98   0.331    -43.79581    128.3842
       55 1957  |  -44.19383   69.39768    -0.64   0.526    -182.1987    93.81107
       55 1958  |  -70.47978    73.4166    -0.96   0.340    -216.4767    75.51717
       55 1959  |  -51.54126   68.70671    -0.75   0.455    -188.1721    85.08956
       55 1960  |  -30.36482   65.08268    -0.47   0.642    -159.7889    99.05923
       55 1961  |  -44.35858   64.21134    -0.69   0.492    -172.0499    83.33271
       55 1962  |  -106.7234   73.47319    -1.45   0.150    -252.8329    39.38605
       56 1957  |  -71.40658    104.471    -0.68   0.496    -279.1586    136.3455
       56 1958  |  -81.58055   103.8862    -0.79   0.434    -288.1697    125.0086
       56 1959  |  -97.46666   108.5609    -0.90   0.372    -313.3518    118.4185
       56 1960  |  -112.8173    109.304    -1.03   0.305    -330.1803    104.5457
       56 1961  |  -100.7317   106.6772    -0.94   0.348    -312.8711    111.4076
       56 1962  |  -95.91979    104.647    -0.92   0.362    -304.0219    112.1823
                |
  c.year#c.laty |   .0002827   .0029923     0.09   0.925    -.0056679    .0062332
                |
  c.year#c.lony |   .0017969   .0023821     0.75   0.453    -.0029401    .0065339
                |
          yprcp |  -.0760738    .043208    -1.76   0.082    -.1619976    .0098499
           ytav |    9.33096   12.15459     0.77   0.445    -14.83978     33.5017
         ydda29 |   .3011244   .2826264     1.07   0.290    -.2609091    .8631578
         yddb10 |   .0506651   .0675644     0.75   0.455    -.0836941    .1850244
      cap30mile |   2.324536   1.022847     2.27   0.026     .2904915     4.35858
          _cons |   344.0109   476.4553     0.72   0.472    -603.4726    1291.494
---------------------------------------------------------------------------------

. local n_counties = e(N_clust)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mile) nocons /*
> */ ctitle(ATA2_c1) se bdec(3) sdec(3) rdec(3) addstat("n_counties", `n_counties') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reg tsp i.state_fips#i.year /*
> */ $Geo /*
> */ cap50mile /*
> */ , cluster(county_fips) 
note: 1b.state_fips#1958.year identifies no observations in the sample
note: 4.state_fips#1958.year identifies no observations in the sample
note: 10.state_fips#1958.year identifies no observations in the sample
note: 10.state_fips#1959.year identifies no observations in the sample
note: 11.state_fips#1957b.year identifies no observations in the sample
note: 13.state_fips#1958.year identifies no observations in the sample
note: 17.state_fips#1957b.year identifies no observations in the sample
note: 17.state_fips#1959.year identifies no observations in the sample
note: 20.state_fips#1958.year identifies no observations in the sample
note: 23.state_fips#1957b.year identifies no observations in the sample
note: 26.state_fips#1958.year identifies no observations in the sample
note: 28.state_fips#1961.year identifies no observations in the sample
note: 32.state_fips#1957b.year identifies no observations in the sample
note: 32.state_fips#1958.year identifies no observations in the sample
note: 33.state_fips#1957b.year identifies no observations in the sample
note: 33.state_fips#1958.year identifies no observations in the sample
note: 34.state_fips#1957b.year identifies no observations in the sample
note: 36.state_fips#1958.year identifies no observations in the sample
note: 37.state_fips#1962.year identifies no observations in the sample
note: 49.state_fips#1957b.year identifies no observations in the sample

Linear regression                               Number of obs     =        433
                                                F(48, 84)         =          .
                                                Prob > F          =          .
                                                R-squared         =     0.7529
                                                Root MSE          =     38.304

                              (Std. Err. adjusted for 85 clusters in county_fips)
---------------------------------------------------------------------------------
                |               Robust
            tsp |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
state_fips#year |
        1 1958  |          0  (empty)
        1 1959  |    13.0258   5.810036     2.24   0.028     1.471907    24.57969
        1 1960  |  -24.60658   15.83738    -1.55   0.124    -56.10094    6.887783
        1 1961  |   3.363141   18.13736     0.19   0.853    -32.70499    39.43127
        1 1962  |  -41.23462    15.3641    -2.68   0.009    -71.78783   -10.68141
        4 1957  |  -36.92779   142.3024    -0.26   0.796    -319.9116     246.056
        4 1958  |          0  (empty)
        4 1959  |   -66.3793   146.5506    -0.45   0.652    -357.8112    225.0526
        4 1960  |  -158.5144   148.6424    -1.07   0.289     -454.106    137.0772
        4 1961  |  -140.2574   145.3489    -0.96   0.337    -429.2996    148.7849
        4 1962  |  -149.1738     145.36    -1.03   0.308     -438.238    139.8905
        5 1957  |   -2.07567   26.16148    -0.08   0.937    -54.10065    49.94931
        5 1958  |  -30.75055   26.55323    -1.16   0.250    -83.55456    22.05346
        5 1959  |  -48.36315   30.47875    -1.59   0.116    -108.9735    12.24719
        5 1960  |  -66.32958   32.10852    -2.07   0.042    -130.1809   -2.478279
        5 1961  |  -58.38141   28.62793    -2.04   0.045    -115.3112   -1.451637
        5 1962  |  -82.48201   37.77082    -2.18   0.032    -157.5934   -7.370587
        6 1957  |   34.10843   141.9213     0.24   0.811    -248.1176    316.3345
        6 1958  |   26.02295   143.3109     0.18   0.856    -258.9664    311.0123
        6 1959  |   16.92044   147.5457     0.11   0.909    -276.4904    310.3312
        6 1960  |   -11.5896   148.6023    -0.08   0.938    -307.1016    283.9224
        6 1961  |  -37.43004   149.0631    -0.25   0.802    -333.8583    258.9983
        6 1962  |   -11.7996      147.9    -0.08   0.937     -305.915    282.3158
        8 1957  |   42.65596   87.24192     0.49   0.626    -130.8342    216.1461
        8 1958  |   5.007277   88.25969     0.06   0.955    -170.5068    180.5214
        8 1959  |   36.20923      89.98     0.40   0.688    -142.7259    215.1443
        8 1960  |   13.91537   93.01262     0.15   0.881    -171.0504    198.8812
        8 1961  |   12.73487   90.29703     0.14   0.888    -166.8307    192.3004
        8 1962  |  -34.36816   95.70297    -0.36   0.720     -224.684    155.9477
        9 1957  |  -93.82066   81.53709    -1.15   0.253    -255.9661    68.32478
        9 1958  |  -90.22188   82.47204    -1.09   0.277    -254.2266    73.78281
        9 1959  |  -100.3826   79.02111    -1.27   0.207    -257.5248    56.75952
        9 1960  |  -99.56926   82.75046    -1.20   0.232    -264.1276     64.9891
        9 1961  |   -128.579   79.98183    -1.61   0.112    -287.6316    30.47366
        9 1962  |  -114.3391   86.64597    -1.32   0.191    -286.6441    57.96589
       10 1957  |  -53.20512   63.05432    -0.84   0.401    -178.5955    72.18531
       10 1958  |          0  (empty)
       10 1959  |          0  (empty)
       10 1960  |   -12.6479   61.80427    -0.20   0.838    -135.5525    110.2567
       10 1961  |  -56.57259   63.21055    -0.89   0.373    -182.2737    69.12852
       10 1962  |   -128.143   67.98302    -1.88   0.063    -263.3347    7.048647
       11 1957  |          0  (empty)
       11 1958  |  -92.94419   54.36871    -1.71   0.091    -201.0623    15.17395
       11 1959  |  -117.8536    54.1945    -2.17   0.032    -225.6253   -10.08189
       11 1960  |  -94.11735   54.36447    -1.73   0.087    -202.2271    13.99236
       11 1961  |  -89.42764   53.63896    -1.67   0.099    -196.0946    17.23931
       11 1962  |  -157.6601   56.36262    -2.80   0.006    -269.7434   -45.57687
       12 1957  |  -80.98508    50.3844    -1.61   0.112      -181.18    19.20983
       12 1958  |  -85.68059   40.97371    -2.09   0.040    -167.1613   -4.199873
       12 1959  |  -41.71625   55.18128    -0.76   0.452    -151.4503    68.01779
       12 1960  |  -75.51463   43.95466    -1.72   0.089    -162.9233    11.89403
       12 1961  |  -133.3717   49.00225    -2.72   0.008     -230.818   -35.92535
       12 1962  |  -124.9165   42.54929    -2.94   0.004    -209.5304   -40.30259
       13 1957  |  -46.68772    12.8154    -3.64   0.000    -72.17254   -21.20289
       13 1958  |          0  (empty)
       13 1959  |  -38.21151   16.42346    -2.33   0.022    -70.87137   -5.551653
       13 1960  |  -53.20318   22.80651    -2.33   0.022    -98.55643   -7.849933
       13 1961  |  -49.49519   21.40906    -2.31   0.023    -92.06946   -6.920919
       13 1962  |  -70.79969   16.88696    -4.19   0.000    -104.3813   -37.21811
       17 1957  |          0  (empty)
       17 1958  |   -64.3152   59.87559    -1.07   0.286    -183.3844    54.75398
       17 1959  |          0  (empty)
       17 1960  |  -94.21192   65.04491    -1.45   0.151    -223.5609    35.13702
       17 1961  |  -68.74601   59.92649    -1.15   0.255    -187.9164     50.4244
       17 1962  |  -185.6363   72.25661    -2.57   0.012    -329.3265   -41.94609
       18 1957  |    58.8759   47.25208     1.25   0.216    -35.09005    152.8418
       18 1958  |  -5.664877   84.52078    -0.07   0.947    -173.7437     162.414
       18 1959  |  -25.59559   49.41381    -0.52   0.606    -123.8604    72.66919
       18 1960  |  -58.07151   77.29343    -0.75   0.455     -211.778    95.63494
       18 1961  |  -76.98436   75.79344    -1.02   0.313    -227.7079     73.7392
       18 1962  |  -73.70759   71.53489    -1.03   0.306    -215.9626    68.54739
       19 1957  |   22.36217   56.00799     0.40   0.691    -89.01587    133.7402
       19 1958  |   19.86405   56.58392     0.35   0.726    -92.65928    132.3874
       19 1959  |  -12.59434   77.99621    -0.16   0.872    -167.6984    142.5097
       19 1960  |    -35.344   100.2486    -0.35   0.725    -234.6994    164.0114
       19 1961  |  -41.29929   67.46285    -0.61   0.542    -175.4566    92.85799
       19 1962  |  -65.08935   73.68412    -0.88   0.380    -211.6183    81.43961
       20 1957  |  -38.65468   52.42113    -0.74   0.463    -142.8998    65.59048
       20 1958  |          0  (empty)
       20 1959  |  -35.25484   52.93327    -0.67   0.507    -140.5184    70.00878
       20 1960  |  -40.80473    58.3438    -0.70   0.486    -156.8278    75.21831
       20 1961  |  -47.14733   52.80279    -0.89   0.374    -152.1515    57.85681
       20 1962  |  -65.51615   58.85757    -1.11   0.269    -182.5609    51.52859
       23 1957  |          0  (empty)
       23 1958  |  -50.11971   99.53329    -0.50   0.616    -248.0526    147.8132
       23 1959  |  -109.9701   104.5487    -1.05   0.296    -317.8767    97.93641
       23 1960  |  -115.4757    106.823    -1.08   0.283     -327.905    96.95349
       23 1961  |  -121.3434   103.6172    -1.17   0.245    -327.3976    84.71077
       23 1962  |  -115.0405   108.4454    -1.06   0.292    -330.6961     100.615
       24 1957  |  -66.79208   56.87314    -1.17   0.244    -179.8906    46.30639
       24 1958  |  -69.97693   56.09582    -1.25   0.216    -181.5296    41.57576
       24 1959  |  -121.5471   79.23958    -1.53   0.129    -279.1237    36.02944
       24 1960  |  -112.3606   71.88877    -1.56   0.122    -255.3194    30.59806
       24 1961  |  -120.5949   68.53633    -1.76   0.082    -256.8869    15.69715
       24 1962  |  -141.5046   66.51022    -2.13   0.036    -273.7675   -9.241769
       25 1957  |   -119.455   90.60982    -1.32   0.191    -299.6426    60.73254
       25 1958  |  -88.58738   91.05808    -0.97   0.333    -269.6664     92.4916
       25 1959  |  -97.60035   88.35519    -1.10   0.272    -273.3043    78.10364
       25 1960  |  -121.9372   89.66497    -1.36   0.177    -300.2458    56.37142
       25 1961  |  -127.0153   86.90865    -1.46   0.148    -299.8427    45.81204
       25 1962  |   -117.115   89.09451    -1.31   0.192    -294.2892    60.05923
       26 1957  |  -75.30786   55.67098    -1.35   0.180    -186.0157    35.39998
       26 1958  |          0  (empty)
       26 1959  |  -79.78839   55.45574    -1.44   0.154    -190.0682    30.49142
       26 1960  |   -122.176   63.17535    -1.93   0.056    -247.8071     3.45509
       26 1961  |  -128.6253   58.24238    -2.21   0.030    -244.4466    -12.8039
       26 1962  |  -161.3352   64.80431    -2.49   0.015    -290.2057   -32.46476
       27 1957  |  -6.104584   68.41976    -0.09   0.929    -142.1648    129.9556
       27 1958  |  -39.25585   68.26292    -0.58   0.567    -175.0042    96.49246
       27 1959  |  -37.12881   71.03701    -0.52   0.603    -178.3937    104.1361
       27 1960  |  -71.37478   74.29797    -0.96   0.339    -219.1244    76.37489
       27 1961  |  -79.21249   70.36364    -1.13   0.263    -219.1383    60.71334
       27 1962  |  -70.30919   74.82213    -0.94   0.350    -219.1012    78.48282
       28 1957  |  -64.51276   27.61495    -2.34   0.022    -119.4281   -9.597411
       28 1958  |  -35.72255    23.5658    -1.52   0.133    -82.58574    11.14064
       28 1959  |  -53.76548   25.97227    -2.07   0.042    -105.4142   -2.116771
       28 1960  |  -73.49558    26.8256    -2.74   0.008    -126.8412   -20.14992
       28 1961  |          0  (empty)
       28 1962  |  -99.10051   35.86099    -2.76   0.007     -170.414     -27.787
       29 1957  |   30.60703   34.49656     0.89   0.377    -37.99316    99.20723
       29 1958  |   27.15117   44.17495     0.61   0.540    -60.69557    114.9979
       29 1959  |   10.24861   51.24429     0.20   0.842    -91.65627    112.1535
       29 1960  |  -24.32275   47.64825    -0.51   0.611    -119.0765    70.43102
       29 1961  |   -12.0961   37.51286    -0.32   0.748    -86.69454    62.50234
       29 1962  |  -39.44908   44.07961    -0.89   0.373    -127.1062    48.20805
       31 1957  |  -11.80418   57.98717    -0.20   0.839     -127.118    103.5097
       31 1958  |  -62.17662   75.75206    -0.82   0.414    -212.8179    88.46467
       31 1959  |   -27.4735   104.9904    -0.26   0.794    -236.2584    181.3114
       31 1960  |  -69.73367   82.74095    -0.84   0.402    -234.2731    94.80578
       31 1961  |  -73.54543   76.20418    -0.97   0.337    -225.0858    77.99495
       31 1962  |  -63.67955   73.04055    -0.87   0.386    -208.9287    81.56959
       32 1957  |          0  (empty)
       32 1958  |          0  (empty)
       32 1959  |  -89.46755   133.9324    -0.67   0.506    -355.8068    176.8717
       32 1960  |  -88.28108   135.7442    -0.65   0.517    -358.2233    181.6611
       32 1961  |   -91.8932   135.4517    -0.68   0.499    -361.2538    177.4674
       32 1962  |  -85.71257   135.1817    -0.63   0.528    -354.5361     183.111
       33 1957  |          0  (empty)
       33 1958  |          0  (empty)
       33 1959  |  -157.1128   103.1277    -1.52   0.131    -362.1936    47.96794
       33 1960  |  -163.0349    104.337    -1.56   0.122    -370.5204    44.45064
       33 1961  |  -171.4963   102.6314    -1.67   0.098    -375.5901    32.59749
       33 1962  |  -153.6187   106.1364    -1.45   0.152    -364.6826    57.44509
       34 1957  |          0  (empty)
       34 1958  |  -204.2887   80.58085    -2.54   0.013    -364.5325   -44.04482
       34 1959  |  -195.5374   76.09655    -2.57   0.012    -346.8637   -44.21103
       34 1960  |  -229.8551   81.05543    -2.84   0.006    -391.0427   -68.66749
       34 1961  |  -266.6999   83.98769    -3.18   0.002    -433.7186   -99.68112
       34 1962  |  -308.0832   92.22734    -3.34   0.001    -491.4874    -124.679
       35 1957  |   80.08199   105.3021     0.76   0.449    -129.3227    289.4867
       35 1958  |    53.2515   104.0101     0.51   0.610     -153.584     260.087
       35 1959  |   111.3285   107.6465     1.03   0.304    -102.7383    325.3953
       35 1960  |    107.398   110.2729     0.97   0.333    -111.8919    326.6878
       35 1961  |   51.01411   110.8516     0.46   0.647    -169.4266    271.4548
       35 1962  |   29.08072   108.0622     0.27   0.789    -185.8128    243.9743
       36 1957  |  -68.40828   77.03821    -0.89   0.377    -221.6072    84.79065
       36 1958  |          0  (empty)
       36 1959  |  -67.55154    75.8617    -0.89   0.376    -218.4109    83.30777
       36 1960  |  -85.81616    76.6178    -1.12   0.266    -238.1791    66.54674
       36 1961  |  -91.74128   76.97758    -1.19   0.237    -244.8196    61.33709
       36 1962  |  -84.76218    77.9175    -1.09   0.280    -239.7097    70.18532
       37 1957  |  -58.89238   30.39214    -1.94   0.056    -119.3305     1.54573
       37 1958  |  -73.53643   30.88111    -2.38   0.020    -134.9469   -12.12595
       37 1959  |  -52.31111   27.89471    -1.88   0.064    -107.7828    3.160586
       37 1960  |  -78.86882   29.01537    -2.72   0.008    -136.5691   -21.16858
       37 1961  |  -56.23551   31.27579    -1.80   0.076    -118.4308    5.959816
       37 1962  |          0  (empty)
       38 1957  |   -32.6637    95.2671    -0.34   0.733    -222.1128    156.7854
       38 1958  |  -84.64833   102.4984    -0.83   0.411    -288.4776     119.181
       38 1959  |  -89.51353   103.7059    -0.86   0.391     -295.744     116.717
       38 1960  |  -67.44362   104.6908    -0.64   0.521    -275.6328    140.7455
       38 1961  |  -88.66104   102.6322    -0.86   0.390    -292.7564    115.4343
       38 1962  |  -63.07327   97.25961    -0.65   0.518    -256.4847    130.3381
       39 1957  |  -15.33406    53.4456    -0.29   0.775    -121.6165    90.94838
       39 1958  |  -42.40051    55.1256    -0.77   0.444    -152.0238     67.2228
       39 1959  |  -29.55012   46.55511    -0.63   0.527    -122.1301    63.02982
       39 1960  |  -60.88263   51.47332    -1.18   0.240     -163.243    41.47772
       39 1961  |  -67.42206    48.4193    -1.39   0.167    -163.7092    28.86504
       39 1962  |  -81.05339   51.25779    -1.58   0.118    -182.9851    20.87835
       42 1957  |  -47.85257   64.41352    -0.74   0.460    -175.9459    80.24077
       42 1958  |  -88.58878   65.29667    -1.36   0.179    -218.4384    41.26081
       42 1959  |  -40.92693   84.87298    -0.48   0.631    -209.7062    127.8523
       42 1960  |  -102.8694    60.9336    -1.69   0.095    -224.0426     18.3037
       42 1961  |   -120.235    60.2884    -1.99   0.049     -240.125   -.3448541
       42 1962  |  -125.6093   63.92704    -1.96   0.053    -252.7353    1.516579
       44 1957  |  -112.2762   87.19662    -1.29   0.201    -285.6763    61.12384
       44 1958  |  -71.34121   88.32539    -0.81   0.422    -246.9859    104.3035
       44 1959  |  -115.8229   88.56465    -1.31   0.195    -291.9434    60.29764
       44 1960  |  -123.7769   93.13017    -1.33   0.187    -308.9764    61.42269
       44 1961  |  -146.5525   84.94503    -1.73   0.088     -315.475       22.37
       44 1962  |  -132.3551   89.59462    -1.48   0.143    -310.5239    45.81361
       45 1957  |  -51.69198   30.11007    -1.72   0.090    -111.5692    8.185194
       45 1958  |  -58.02889   26.21022    -2.21   0.030    -110.1508   -5.906989
       45 1959  |  -106.3355   29.18427    -3.64   0.000    -164.3716   -48.29939
       45 1960  |  -85.38664   25.49212    -3.35   0.001    -136.0805   -34.69276
       45 1961  |  -112.9675   26.35896    -4.29   0.000    -165.3852    -60.5498
       45 1962  |  -98.71468   26.18939    -3.77   0.000    -150.7952    -46.6342
       46 1957  |  -47.41954   71.48977    -0.66   0.509    -189.5848     94.7457
       46 1958  |  -36.73196   75.15718    -0.49   0.626    -186.1903    112.7263
       46 1959  |  -44.12258   75.35136    -0.59   0.560     -193.967    105.7219
       46 1960  |   -30.8137   80.04147    -0.38   0.701    -189.9849    128.3575
       46 1961  |  -77.31972   74.75018    -1.03   0.304    -225.9686    71.32921
       46 1962  |  -40.10842   74.00269    -0.54   0.589    -187.2709    107.0541
       47 1957  |   9.799663   11.76863     0.83   0.407    -13.60354    33.20287
       47 1958  |   24.44663   53.89834     0.45   0.651    -82.73614    131.6294
       47 1959  |   38.01389   25.83627     1.47   0.145    -13.36437    89.39215
       47 1960  |  -17.92211   47.79823    -0.37   0.709    -112.9741    77.12992
       47 1961  |   5.395466   56.27863     0.10   0.924    -106.5208    117.3117
       47 1962  |  -7.080121   33.59705    -0.21   0.834    -73.89153    59.73129
       48 1957  |  -37.78144   65.97632    -0.57   0.568    -168.9826    93.41971
       48 1958  |  -84.97689   70.27072    -1.21   0.230    -224.7179    54.76415
       48 1959  |  -43.79001   65.44239    -0.67   0.505    -173.9294    86.34936
       48 1960  |  -66.70554   69.34113    -0.96   0.339     -204.598     71.1869
       48 1961  |  -68.56525   63.19448    -1.08   0.281    -194.2344     57.1039
       48 1962  |  -122.6526    64.4009    -1.90   0.060    -250.7208    5.415675
       49 1957  |          0  (empty)
       49 1958  |  -6.255244   113.9014    -0.05   0.956    -232.7606    220.2501
       49 1959  |   18.45885   113.4545     0.16   0.871    -207.1579    244.0756
       49 1960  |   10.52597   116.0451     0.09   0.928    -220.2424    241.2943
       49 1961  |   38.15745   116.0786     0.33   0.743    -192.6776    268.9925
       49 1962  |   48.52153   115.4084     0.42   0.675    -180.9808    278.0239
       50 1957  |  -132.4553   90.30009    -1.47   0.146    -312.0269    47.11636
       50 1958  |  -132.3873   92.28347    -1.43   0.155    -315.9031     51.1285
       50 1959  |  -131.8321   89.68736    -1.47   0.145    -310.1853    46.52104
       50 1960  |  -139.2834    91.5571    -1.52   0.132    -321.3548     42.7879
       50 1961  |  -129.3546   92.11732    -1.40   0.164    -312.5399    53.83082
       50 1962  |  -131.1945   93.54066    -1.40   0.164    -317.2104    54.82135
       51 1957  |  -70.15623   53.62723    -1.31   0.194    -176.7999    36.48741
       51 1958  |  -89.21535   68.93459    -1.29   0.199    -226.2993    47.86864
       51 1959  |  -101.9331   62.50294    -1.63   0.107     -226.227    22.36088
       51 1960  |  -117.0035   52.77655    -2.22   0.029    -221.9554   -12.05153
       51 1961  |   -109.475   52.24105    -2.10   0.039     -213.362   -5.587908
       51 1962  |  -105.1241   56.82591    -1.85   0.068    -218.1286     7.88048
       54 1957  |   18.99102   39.41647     0.48   0.631    -59.39297      97.375
       54 1958  |   20.40365   40.85057     0.50   0.619    -60.83219    101.6395
       54 1959  |   48.17177   39.53164     1.22   0.226    -30.44123    126.7848
       54 1960  |   20.11203   42.04575     0.48   0.634    -63.50056    103.7246
       54 1961  |   28.17766   40.67077     0.69   0.490    -52.70063    109.0559
       54 1962  |   34.84052   39.78319     0.88   0.384    -44.27272    113.9538
       55 1957  |  -23.55299   58.26875    -0.40   0.687    -139.4268     92.3208
       55 1958  |  -53.39464   61.47561    -0.87   0.388    -175.6456    68.85636
       55 1959  |  -35.89301   58.47989    -0.61   0.541    -152.1867    80.40066
       55 1960  |   -21.0721   56.59826    -0.37   0.711    -133.6239    91.47975
       55 1961  |  -33.94128   55.14753    -0.62   0.540    -143.6082    75.72563
       55 1962  |  -97.98466   62.83496    -1.56   0.123    -222.9389    26.96954
       56 1957  |  -59.45656   91.97218    -0.65   0.520    -242.3533    123.4402
       56 1958  |  -66.37011   91.53999    -0.73   0.470    -248.4074    115.6672
       56 1959  |  -80.00601   94.69969    -0.84   0.401    -268.3267    108.3147
       56 1960  |  -93.37483   95.46131    -0.98   0.331    -283.2101    96.46045
       56 1961  |  -86.40229   93.56379    -0.92   0.358    -272.4641    99.65956
       56 1962  |  -81.81969    92.4882    -0.88   0.379    -265.7426    102.1032
                |
  c.year#c.laty |  -.0009678   .0026417    -0.37   0.715    -.0062211    .0042855
                |
  c.year#c.lony |   .0014667   .0021752     0.67   0.502     -.002859    .0057924
                |
          yprcp |  -.0611906   .0372315    -1.64   0.104    -.1352296    .0128484
           ytav |   3.668253   11.70659     0.31   0.755    -19.61159    26.94809
         ydda29 |     .51588   .2774966     1.86   0.067    -.0359524    1.067712
         yddb10 |   .0235268   .0569346     0.41   0.680    -.0896939    .1367474
      cap50mile |   2.237797   .6451007     3.47   0.001     .9549432     3.52065
          _cons |   452.8598   459.2216     0.99   0.327    -460.3527    1366.072
---------------------------------------------------------------------------------

. local n_counties = e(N_clust)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap50mile) nocons /*
> */ ctitle(ATA2_c2) se bdec(3) sdec(3) rdec(3) addstat("n_counties", `n_counties') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***BOTTOM ROWS
. ****************************************
. *Mean dep var (TSP) -- 1957
. sum tsp if year==1957

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         tsp |         53    141.0081    52.70804      53.28     306.05

. local avg_tsp_1957 = r(mean)

. di `avg_tsp_1957'
141.00809

. 
. *Mean dep var (TSP) -- 1962
. sum tsp if year==1962

    Variable |        Obs        Mean    Std. Dev.       Min        Max
-------------+---------------------------------------------------------
         tsp |         81    100.0387    43.28511    19.2692   219.0952

. local avg_tsp_1962 = r(mean)

. di `avg_tsp_1962'
100.03873

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX TABLE A.3
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. *creating intermediate variables
. gen treat_bigsmall = 1 if treat==1 & bcap1940==1
(120,275 missing values generated)

. replace treat_bigsmall = 2 if treat==1 & scap1940==1
(14,675 real changes made)

. 
. *adjusting units of variables
. replace pop = pop/1000
variable pop was long now double
(15,840 real changes made)

. replace spopurb = spopurb*100
(11,541 real changes made)

. replace emp = emp/1000
(15,840 real changes made)

. replace smfg = smfg*100
(15,838 real changes made)

. replace f_coalq = f_coalq/100
(38,334 real changes made)

. replace cap30mile_hydro = cap30mile_hydro*100
(33,734 real changes made)

. *cap30mile_hydro was measured in 100s of MWs
. 
. *generating access to electricity based on percent of
. *households with lighting
. gen elec = light*100
(121,440 missing values generated)

. replace elec = 100 if year==1960
(5,280 real changes made)

. 
. 
. ****************************************
. ***PANEL A
. ****************************************
. *number of plants (for big vs. small cap1940, and total)
. sort idcountyplant plant_id county_fips year

. bysort treat plant_id: gen n_plant = _n

. tab treat_bigsmall if n_plant==1

treat_bigsm |
        all |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |         96       35.56       35.56
          2 |        174       64.44      100.00
------------+-----------------------------------
      Total |        270      100.00

. 
. *initial year of operation
. table control if year==1940 [fw=births_rs], c(mean cinityropr) format(%12.0f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    | mean(cini~r)
----------+-------------
        0 |         1952
        1 |         1952
          | 
    Total |         1952
------------------------

. table treat_bigsmall if year==1940 [fw=births_rs], c(mean cinityropr) format(%12.0f)

------------------------
treat_big |
small     | mean(cini~r)
----------+-------------
        1 |         1952
        2 |         1952
------------------------

. 
. *capacity
. table control if post>=0 [fw=births_rs], c(mean ccapacity) format(%12.1f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    | mean(ccap~y)
----------+-------------
        0 |        140.9
        1 |        115.3
          | 
    Total |        127.4
------------------------

. table treat_bigsmall if post>=0 [fw=births_rs], c(mean ccapacity) format(%12.1f)

------------------------
treat_big |
small     | mean(ccap~y)
----------+-------------
        1 |        151.9
        2 |         90.7
------------------------

. 
. *annual coal consumption
. table control [fw=births_rs], c(mean f_coalq) format(%12.1f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    | mean(f_co~q)
----------+-------------
        0 |          6.8
        1 |          6.2
          | 
    Total |          6.5
------------------------

. table treat_bigsmall [fw=births_rs], c(mean f_coalq) format(%12.1f) row

------------------------
treat_big |
small     | mean(f_co~q)
----------+-------------
        1 |          7.2
        2 |          4.2
          | 
    Total |          6.8
------------------------

. 
. 
. ****************************************
. ***PANEL B
. ****************************************
. *infant mortality rate
. table control [fw=births_rs], c(mean imr) format(%12.1f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    |    mean(imr)
----------+-------------
        0 |         29.1
        1 |         31.1
          | 
    Total |         30.2
------------------------

. table treat_bigsmall [fw=births_rs], c(mean imr) format(%12.1f)

------------------------
treat_big |
small     |    mean(imr)
----------+-------------
        1 |         28.6
        2 |         31.4
------------------------

. 
. *distance to power plant
. table control [fw=births_rs], c(mean dist_miles) format(%12.1f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    | mean(dist~s)
----------+-------------
        0 |         18.0
        1 |         64.4
          | 
    Total |         42.6
------------------------

. table treat_bigsmall [fw=births_rs], c(mean dist_miles) format(%12.1f)

------------------------
treat_big |
small     | mean(dist~s)
----------+-------------
        1 |         18.0
        2 |         18.2
------------------------

. 
. *hydroelectric capacity
. table control [fw=births_rs], c(mean cap30mile_hydro) format(%12.0f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    | mean(cap3~o)
----------+-------------
        0 |           19
        1 |           22
          | 
    Total |           21
------------------------

. table treat_bigsmall [fw=births_rs], c(mean cap30mile_hydro) format(%12.0f)

------------------------
treat_big |
small     | mean(cap3~o)
----------+-------------
        1 |           22
        2 |            8
------------------------

. 
. *baseline characteristics
. *employment
. table control if year==1940 [fw=births_rs], c(mean emp) format(%12.0f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    |    mean(emp)
----------+-------------
        0 |          320
        1 |           34
          | 
    Total |          154
------------------------

. table treat_bigsmall if year==1940 [fw=births_rs], c(mean emp) format(%12.0f)

------------------------
treat_big |
small     |    mean(emp)
----------+-------------
        1 |          395
        2 |           26
------------------------

. 
. *% manufacturing employment
. table control if year==1940 [fw=births_rs], c(mean smfg) format(%12.1f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    |   mean(smfg)
----------+-------------
        0 |         29.1
        1 |         19.6
          | 
    Total |         23.6
------------------------

. table treat_bigsmall if year==1940 [fw=births_rs], c(mean smfg) format(%12.1f) row

------------------------
treat_big |
small     |   mean(smfg)
----------+-------------
        1 |         32.0
        2 |         18.0
          | 
    Total |         29.1
------------------------

. 
. *population
. table control if year==1940 [fw=births_rs], c(mean pop) format(%12.0f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    |    mean(pop)
----------+-------------
        0 |          842
        1 |          102
          | 
    Total |          413
------------------------

. table treat_bigsmall if year==1940 [fw=births_rs], c(mean pop) format(%12.0f)

------------------------
treat_big |
small     |    mean(pop)
----------+-------------
        1 |         1037
        2 |           76
------------------------

. 
. *% urban
. table control if year==1940 [fw=births_rs], c(mean spopurb) format(%12.1f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    | mean(spop~b)
----------+-------------
        0 |         70.3
        1 |         38.4
          | 
    Total |         51.8
------------------------

. table treat_bigsmall if year==1940 [fw=births_rs], c(mean spopurb) format(%12.1f) row

------------------------
treat_big |
small     | mean(spop~b)
----------+-------------
        1 |         78.2
        2 |         39.2
          | 
    Total |         70.3
------------------------

. 
. *% households with electricity
. table control if year==1940 [fw=births_rs], c(mean elec) format(%12.1f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    |   mean(elec)
----------+-------------
        0 |         88.4
        1 |         66.9
          | 
    Total |         76.0
------------------------

. table treat_bigsmall if year==1940 [fw=births_rs], c(mean elec) format(%12.1f) row

------------------------
treat_big |
small     |   mean(elec)
----------+-------------
        1 |         94.1
        2 |         66.3
          | 
    Total |         88.4
------------------------

. 
. *railroad mileage
. table control if year==1940 [fw=births_rs], c(mean railroads) format(%12.1f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    | mean(rail~s)
----------+-------------
        0 |        198.7
        1 |        112.4
          | 
    Total |        148.7
------------------------

. table treat_bigsmall if year==1940 [fw=births_rs], c(mean railroads) format(%12.1f) row

------------------------
treat_big |
small     | mean(rail~s)
----------+-------------
        1 |        219.4
        2 |        117.7
          | 
    Total |        198.7
------------------------

. 
. *predicted interstate highway
. table control if year==1940 [fw=births_rs], c(mean inst1944) format(%12.2f) row

------------------------
County    |
30-90     |
miles     |
from      |
power     |
plants    | mean(i~1944)
----------+-------------
        0 |         0.80
        1 |         0.50
          | 
    Total |         0.62
------------------------

. table treat_bigsmall if year==1940 [fw=births_rs], c(mean inst1944) format(%12.2f) row

------------------------
treat_big |
small     | mean(i~1944)
----------+-------------
        1 |         0.87
        2 |         0.49
          | 
    Total |         0.80
------------------------

. 
. 
. ****************************************
. ***BOTTOM ROWS
. ****************************************
. *number of counties
. sort idcountyplant plant_id county_fips year

. bysort county_fips: gen n_county1 = _n

. tab control if n_county1==1

     County |
30-90 miles |
 from power |
     plants |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |        734       37.28       37.28
          1 |      1,235       62.72      100.00
------------+-----------------------------------
      Total |      1,969      100.00

. *number of counties for big vs small cap1940
. sort idcountyplant plant_id county_fips year

. bysort treat county_fips: gen n_county2 = _n

. tab treat_bigsmall if n_county2==1

treat_bigsm |
        all |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        251       34.20       34.20
          2 |        483       65.80      100.00
------------+-----------------------------------
      Total |        734      100.00

. 
. *number of county-plant pairs
. sort idcountyplant plant_id county_fips year

. bysort idcountyplant: gen n_countyplant = _n

. tab control if n_countyplant==1

     County |
30-90 miles |
 from power |
     plants |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |      1,056       20.00       20.00
          1 |      4,224       80.00      100.00
------------+-----------------------------------
      Total |      5,280      100.00

. *number of county-plant pairs for big vs small cap1940
. tab treat_bigsmall if n_countyplant==1

treat_bigsm |
        all |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |        469       44.41       44.41
          2 |        587       55.59      100.00
------------+-----------------------------------
      Total |      1,056      100.00

. 
. *number of observations
. tab control

     County |
30-90 miles |
 from power |
     plants |      Freq.     Percent        Cum.
------------+-----------------------------------
          0 |     26,400       20.00       20.00
          1 |    105,600       80.00      100.00
------------+-----------------------------------
      Total |    132,000      100.00

. *number of observations for big vs small cap1940
. tab treat_bigsmall

treat_bigsm |
        all |      Freq.     Percent        Cum.
------------+-----------------------------------
          1 |     11,725       44.41       44.41
          2 |     14,675       55.59      100.00
------------+-----------------------------------
      Total |     26,400      100.00

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX TABLE A.4
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. *Adjusting units for summary statistics
. replace pop = pop/1000
variable pop was long now double
(6,081 real changes made)

. replace emp = emp/1000
(6,081 real changes made)

. replace mfg = mfg/1000
(6,079 real changes made)

. replace smfg = smfg*100
(6,079 real changes made)

. replace light = light*100
(4,052 real changes made)

. replace spopurb = spopurb*100
(4,269 real changes made)

. replace swhite = swhite*100
(6,081 real changes made)

. replace hschool = hschool*100
(6,081 real changes made)

. 
. gen ccap1940= 1 if bcap1940==1
(39,900 missing values generated)

. replace ccap1940 = 2 if scap1940==1
(39,900 real changes made)

. 
. ****************************************
. ***PANEL A
. ****************************************
. *Infant mortality rate -- Mean
. table ccap1940 [fw=births_rs], c(mean imr) format(%12.1f) row

------------------------
 ccap1940 |    mean(imr)
----------+-------------
        1 |         29.1
        2 |         32.0
          | 
    Total |         30.4
------------------------

. 
. *Infant mortality rate -- Change, 1962-1938
. sort county_fips year

. gen imr_ch = imr - imr[_n-24]
(24 missing values generated)

. replace imr_ch = . if year~=1962
(48,624 real changes made, 48,624 to missing)

. table ccap1940 [fw=births_rs], c(mean imr_ch) format(%12.2f) row

------------------------
 ccap1940 | mean(imr_ch)
----------+-------------
        1 |       -18.49
        2 |       -24.30
          | 
    Total |       -20.88
------------------------

. 
. *Median dwelling value, 1990$
. table ccap1940 [fw=births_rs], c(mean mvhouse_bls90) format(%12.0f) row

------------------------
 ccap1940 | mean(mvh~90)
----------+-------------
        1 |        49532
        2 |        31360
          | 
    Total |        41525
------------------------

. 
. *Manufacturing payroll per worker
. table ccap1940 [fw=births_rs], c(mean mfgwages_bls90) format(%12.1f) row

------------------------
 ccap1940 | mean(mfg~90)
----------+-------------
        1 |         19.8
        2 |         14.9
          | 
    Total |         17.7
------------------------

. 
. *Retail payroll per worker
. table ccap1940 [fw=births_rs], c(mean retwages_bls90) format(%12.1f) row

------------------------
 ccap1940 | mean(ret~90)
----------+-------------
        1 |         13.3
        2 |         11.3
          | 
    Total |         12.5
------------------------

. 
. *% White
. table ccap1940 [fw=births_rs], c(mean swhite) format(%12.1f) row

------------------------
 ccap1940 | mean(swhite)
----------+-------------
        1 |         89.9
        2 |         88.2
          | 
    Total |         89.1
------------------------

. 
. *% High School (age 25+)
. table ccap1940 [fw=births_rs], c(mean hschool) format(%12.1f) row

------------------------
 ccap1940 | mean(hsch~l)
----------+-------------
        1 |         36.9
        2 |         30.3
          | 
    Total |         34.0
------------------------

. 
. ****************************************
. ***PANEL B
. ****************************************
. *Coal capacity <30 miles (100 MWs) -- Mean
. table ccap1940 [fw=births_rs], c(mean cap30mile) format(%12.2f) row

------------------------
 ccap1940 | mean(cap3~e)
----------+-------------
        1 |        10.00
        2 |         0.70
          | 
    Total |         5.94
------------------------

. 
. *Coal capacity <30 miles (100 MWs) -- Change, 1962-1938
. sort county_fips year

. gen cap30mile_ch = cap30mile - cap30mile[_n-24]
(24 missing values generated)

. replace cap30mile_ch = . if year~=1962
(48,624 real changes made, 48,624 to missing)

. table ccap1940 [fw=births_rs], c(mean cap30mile_ch) format(%12.2f) row

------------------------
 ccap1940 | mean(cap3~h)
----------+-------------
        1 |        15.50
        2 |         2.26
          | 
    Total |        10.07
------------------------

. 
. *Coal consumption <30 miles (100K Tons) -- Mean
. table ccap1940 [fw=births_rs], c(mean coal30mile) format(%12.2f) row

------------------------
 ccap1940 | mean(coal~e)
----------+-------------
        1 |        17.35
        2 |         1.05
          | 
    Total |        10.24
------------------------

. 
. *Coal consumption <30 miles (100K Tons) -- Change, 1962-1938
. sort county_fips year

. gen coal30mile_ch = coal30mile - coal30mile[_n-24]
(24 missing values generated)

. replace coal30mile_ch = . if year~=1962
(48,624 real changes made, 48,624 to missing)

. table ccap1940 [fw=births_rs], c(mean coal30mile_ch) format(%12.2f) row

------------------------
 ccap1940 | mean(coal~h)
----------+-------------
        1 |        19.35
        2 |         2.55
          | 
    Total |        12.46
------------------------

. 
. *Hydro capacity <30 miles (100 MWs) -- Mean
. table ccap1940 [fw=births_rs], c(mean cap30mile_hydro) format(%12.2f) row

------------------------
 ccap1940 | mean(cap3~o)
----------+-------------
        1 |         0.40
        2 |         0.12
          | 
    Total |         0.28
------------------------

. 
. *Hydro capacity <30 miles (100 MWs) -- Change, 1962-1938
. sort county_fips year

. gen cap30mile_hydro_ch = cap30mile_hydro - cap30mile_hydro[_n-24]
(24 missing values generated)

. replace cap30mile_hydro_ch = . if year~=1962
(48,624 real changes made, 48,624 to missing)

. table ccap1940 [fw=births_rs], c(mean cap30mile_hydro_ch) format(%12.2f) row

------------------------
 ccap1940 | mean(cap3~h)
----------+-------------
        1 |         0.08
        2 |         0.53
          | 
    Total |         0.26
------------------------

. 
. ****************************************
. ***PANEL C
. ****************************************
. *Population (1,000s)
. table ccap1940 if year==1940 [fw=births_rs], c(mean pop) format(%12.0f) row

------------------------
 ccap1940 |    mean(pop)
----------+-------------
        1 |          835
        2 |           69
          | 
    Total |          456
------------------------

. 
. *% Urban
. table ccap1940 if year==1940 [fw=births_rs], c(mean spopurb) format(%12.1f) row

------------------------
 ccap1940 | mean(spop~b)
----------+-------------
        1 |         70.5
        2 |         33.1
          | 
    Total |         52.0
------------------------

. 
. *Employment (1,000s)
. table ccap1940 if year==1940 [fw=births_rs], c(mean emp) format(%12.0f) row

------------------------
 ccap1940 |    mean(emp)
----------+-------------
        1 |          316
        2 |           23
          | 
    Total |          171
------------------------

. 
. *% Manufacturing Employment
. table ccap1940 if year==1940 [fw=births_rs], c(mean smfg) format(%12.1f) row

------------------------
 ccap1940 |   mean(smfg)
----------+-------------
        1 |         30.0
        2 |         15.8
          | 
    Total |         23.0
------------------------

. 
. *% Households with Electricity 
. table ccap1940 if year==1940 [fw=births_rs], c(mean light) format(%12.1f) row

------------------------
 ccap1940 |  mean(light)
----------+-------------
        1 |         89.2
        2 |         60.3
          | 
    Total |         74.8
------------------------

. 
. *Mileage of Railroads, 1911 
. table ccap1940 if year==1940 [fw=births_rs], c(mean railroads) format(%12.1f) row

------------------------
 ccap1940 | mean(rail~s)
----------+-------------
        1 |        201.0
        2 |        109.5
          | 
    Total |        155.7
------------------------

. 
. *Predicted Interstate Highway, 1944
. table ccap1940 if year==1940 [fw=births_rs], c(mean inst1944) format(%12.2f) row

------------------------
 ccap1940 | mean(i~1944)
----------+-------------
        1 |         0.83
        2 |         0.42
          | 
    Total |         0.63
------------------------

. 
. ****************************************
. ***BOTTOM ROW
. ****************************************
. *Number of Counties
. table ccap1940 if year==1962, format(%12.0f) row

------------------------
 ccap1940 |        Freq.
----------+-------------
        1 |          431
        2 |         1596
          | 
    Total |         2027
------------------------

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX TABLE A.5
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. global Geot1 c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econt1 c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. global Econnlnt1 c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. ****************************************
. ***PANEL A
. ****************************************
. *Baseline estimates
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  17,   1968) =      15.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6785
                                                  Adj R-squared   =     0.6785
                                                  Within R-sq.    =     0.0362
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7751

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0001989   .0003662    -0.54   0.587    -.0009171    .0005193
                    |
          ccapacity |   .0005522   .0002555     2.16   0.031     .0000512    .0010532
                    |
      c.year#c.laty |    .075773   .0119439     6.34   0.000     .0523491     .099197
                    |
      c.year#c.lony |   .0464917   .0089661     5.19   0.000     .0289076    .0640757
                    |
              yprcp |   .0003901   .0003106     1.26   0.209    -.0002191    .0009992
               ytav |   .2914035   .1773787     1.64   0.101    -.0564663    .6392733
             ydda29 |  -.0022367   .0026736    -0.84   0.403    -.0074801    .0030067
             yddb10 |   .0001793   .0007433     0.24   0.809    -.0012784    .0016369
                    |
 c.year#c.lnpop1940 |  -.5737178   .1465213    -3.92   0.000    -.8610709   -.2863646
                    |
 c.year#c.lnemp1940 |   .7057342    .145045     4.87   0.000     .4212763    .9901921
                    |
 c.year#c.lnmfg1940 |  -.0342414   .0237608    -1.44   0.150    -.0808403    .0123575
                    |
 c.year#c.railroads |  -.0002035   .0001848    -1.10   0.271     -.000566     .000159
                    |
  c.year#c.inst1944 |   .0239572    .030214     0.79   0.428    -.0352976     .083212
                    |
 c.year#c.light1940 |  -.9451938    .147773    -6.40   0.000    -1.235002   -.6553858
                    |
    cap30mile_hydro |   .0048784   .0541433     0.09   0.928    -.1013059    .1110626
               post |  -.4449091   .1217639    -3.65   0.000    -.6837089   -.2061094
          treatpost |   .6090359   .1915582     3.18   0.001     .2333576    .9847142
              _cons |   2481.377   1693.956     1.46   0.143    -840.7585    5803.512
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(ATA5_PA_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Weight by females age 15-44
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treatpost /*
> */ [fw=popf15_44], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 1652295469
Absorbing 2 HDFE groups                           F(  17,   1968) =      15.78
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6885
                                                  Adj R-squared   =     0.6885
                                                  Within R-sq.    =     0.0408
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8671

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0003206   .0004125    -0.78   0.437    -.0011296    .0004884
                    |
          ccapacity |   .0007341   .0002788     2.63   0.009     .0001874    .0012808
                    |
      c.year#c.laty |   .0779586   .0129631     6.01   0.000     .0525357    .1033815
                    |
      c.year#c.lony |   .0519662   .0100714     5.16   0.000     .0322145    .0717178
                    |
              yprcp |   .0003816   .0003436     1.11   0.267    -.0002923    .0010555
               ytav |    .347051    .201135     1.73   0.085     -.047409     .741511
             ydda29 |  -.0039091   .0033252    -1.18   0.240    -.0104304    .0026123
             yddb10 |   .0000704   .0008208     0.09   0.932    -.0015393    .0016802
                    |
 c.year#c.lnpop1940 |  -.6227688    .165322    -3.77   0.000    -.9469934   -.2985443
                    |
 c.year#c.lnemp1940 |   .7517919   .1634671     4.60   0.000     .4312051    1.072379
                    |
 c.year#c.lnmfg1940 |   -.038525   .0260964    -1.48   0.140    -.0897045    .0126545
                    |
 c.year#c.railroads |  -.0001478   .0002022    -0.73   0.465    -.0005443    .0002487
                    |
  c.year#c.inst1944 |   .0195905   .0344791     0.57   0.570    -.0480289    .0872099
                    |
 c.year#c.light1940 |  -.9876153   .1643915    -6.01   0.000    -1.310015   -.6652157
                    |
    cap30mile_hydro |  -.0104852    .066334    -0.16   0.874    -.1405775    .1196071
               post |  -.5731756   .1375957    -4.17   0.000    -.8430243    -.303327
          treatpost |   .7019705   .2126726     3.30   0.001     .2848833    1.119058
              _cons |   3477.846   1888.755     1.84   0.066    -226.3226    7182.016
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(ATA5_PA_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Omit counties -- Treated by multiple plants
. capture drop ncy

. bysort county_fips year: gen ncy = _n

. capture drop N

. bysort county_fips treat: gen N = _N

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treatpost /*
> */ if ((treat==1 & N==25) | (treat==0 & ncy==1)) [fw=births_rs], /*
> */ absorb(county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 39,885,256
Absorbing 2 HDFE groups                           F(  17,   1753) =       8.66
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6503
                                                  Adj R-squared   =     0.6503
                                                  Within R-sq.    =     0.0194
Number of clusters (county_fips) =      1,754     Root MSE        =     6.6982

                               (Std. Err. adjusted for 1,754 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |   3.49e-07   1.81e-06     0.19   0.847    -3.19e-06    3.89e-06
                    |
          ccapacity |   .0003589   .0004137     0.87   0.386    -.0004524    .0011703
                    |
      c.year#c.laty |   .0503075   .0139092     3.62   0.000     .0230272    .0775878
                    |
      c.year#c.lony |    .019701   .0079969     2.46   0.014     .0040166    .0353855
                    |
              yprcp |   .0002974   .0002678     1.11   0.267    -.0002278    .0008226
               ytav |   .0890091   .1499977     0.59   0.553    -.2051841    .3832023
             ydda29 |  -.0005088   .0028299    -0.18   0.857    -.0060592    .0050416
             yddb10 |  -.0003611   .0006565    -0.55   0.582    -.0016487    .0009265
                    |
 c.year#c.lnpop1940 |  -.3398202   .1472856    -2.31   0.021    -.6286942   -.0509463
                    |
 c.year#c.lnemp1940 |   .4283565   .1465217     2.92   0.004     .1409808    .7157322
                    |
 c.year#c.lnmfg1940 |  -.0097966    .019654    -0.50   0.618    -.0483442    .0287511
                    |
 c.year#c.railroads |  -.0006326   .0001854    -3.41   0.001    -.0009962   -.0002691
                    |
  c.year#c.inst1944 |   .0443057   .0251038     1.76   0.078    -.0049308    .0935423
                    |
 c.year#c.light1940 |  -1.062567   .1163988    -9.13   0.000    -1.290862   -.8342716
                    |
    cap30mile_hydro |   .0359491   .0523043     0.69   0.492    -.0666363    .1385344
               post |  -.2986429   .1645273    -1.82   0.070    -.6213333    .0240474
          treatpost |   .5507725   .2979437     1.85   0.065    -.0335899    1.135135
              _cons |   266.4709   1705.089     0.16   0.876    -3077.751    3610.693
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      1754        1754           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(ATA5_PA_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Omit counties -- 30-60 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treatpost /*
> */ [fw=births_rs] if (dist_miles<=30 |dist_miles>=60), /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  133774415
Absorbing 2 HDFE groups                           F(  17,   1790) =      20.37
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6943
                                                  Adj R-squared   =     0.6943
                                                  Within R-sq.    =     0.0443
Number of clusters (county_fips) =      1,791     Root MSE        =     5.4135

                               (Std. Err. adjusted for 1,791 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0001202   .0004657    -0.26   0.796    -.0010335    .0007932
                    |
          ccapacity |    .000765   .0002879     2.66   0.008     .0002004    .0013296
                    |
      c.year#c.laty |   .0860998   .0122017     7.06   0.000     .0621688    .1100309
                    |
      c.year#c.lony |   .0545888   .0087235     6.26   0.000     .0374795    .0716981
                    |
              yprcp |   .0003094   .0003003     1.03   0.303    -.0002796    .0008984
               ytav |   .3552059   .1736581     2.05   0.041      .014612    .6957998
             ydda29 |  -.0032215   .0025553    -1.26   0.208    -.0082331    .0017901
             yddb10 |   .0001188   .0007333     0.16   0.871    -.0013195    .0015571
                    |
 c.year#c.lnpop1940 |  -.4911226   .1442386    -3.40   0.001    -.7740164   -.2082288
                    |
 c.year#c.lnemp1940 |   .6519853   .1438219     4.53   0.000     .3699089    .9340617
                    |
 c.year#c.lnmfg1940 |  -.0565018   .0250081    -2.26   0.024    -.1055499   -.0074536
                    |
 c.year#c.railroads |  -.0002042   .0001562    -1.31   0.191    -.0005106    .0001021
                    |
  c.year#c.inst1944 |  -.0005183   .0300438    -0.02   0.986     -.059443    .0584064
                    |
 c.year#c.light1940 |  -.8433287   .1482032    -5.69   0.000    -1.133998   -.5526592
                    |
    cap30mile_hydro |  -.0030624   .0636138    -0.05   0.962    -.1278276    .1217028
               post |  -.5311376   .1388902    -3.82   0.000    -.8035415   -.2587336
          treatpost |   .4825221   .1858482     2.60   0.009     .1180198    .8470243
              _cons |   2475.625   1693.411     1.46   0.144    -845.6458    5796.895
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      3657        3657           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(ATA5_PA_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Alternate treatment radii -- <20 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treat20post /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  17,   1968) =      15.78
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6785
                                                  Adj R-squared   =     0.6785
                                                  Within R-sq.    =     0.0360
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7757

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0004505   .0004099    -1.10   0.272    -.0012544    .0003534
                    |
          ccapacity |   .0005466   .0002539     2.15   0.031     .0000487    .0010445
                    |
      c.year#c.laty |   .0749188   .0120203     6.23   0.000     .0513449    .0984926
                    |
      c.year#c.lony |   .0469707   .0089899     5.22   0.000     .0293399    .0646014
                    |
              yprcp |   .0003913   .0003103     1.26   0.207    -.0002173    .0009998
               ytav |   .2891801   .1772135     1.63   0.103    -.0583656    .6367259
             ydda29 |  -.0022509   .0026838    -0.84   0.402    -.0075142    .0030124
             yddb10 |   .0001689   .0007438     0.23   0.820    -.0012899    .0016277
                    |
 c.year#c.lnpop1940 |  -.5784924   .1467581    -3.94   0.000      -.86631   -.2906748
                    |
 c.year#c.lnemp1940 |   .7113586   .1453319     4.89   0.000      .426338    .9963793
                    |
 c.year#c.lnmfg1940 |   -.034775   .0238352    -1.46   0.145    -.0815199    .0119699
                    |
 c.year#c.railroads |  -.0001998   .0001863    -1.07   0.284    -.0005651    .0001656
                    |
  c.year#c.inst1944 |   .0245662   .0303795     0.81   0.419    -.0350131    .0841455
                    |
 c.year#c.light1940 |  -.9424013   .1486736    -6.34   0.000    -1.233976   -.6508271
                    |
    cap30mile_hydro |   .0015405   .0543534     0.03   0.977    -.1050558    .1081367
               post |  -.2464376   .0995887    -2.47   0.013    -.4417479   -.0511272
        treat20post |   .3344396   .1961475     1.71   0.088     -.050239    .7191182
              _cons |   2641.852   1697.347     1.56   0.120    -686.9341    5970.637
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treat20post) nocons /*
> */ ctitle(ATA5_PA_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Alternate treatment radii -- <40 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treat40post /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  17,   1968) =      15.10
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6785
                                                  Adj R-squared   =     0.6785
                                                  Within R-sq.    =     0.0361
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7756

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |   -.000309   .0004344    -0.71   0.477    -.0011609    .0005429
                    |
          ccapacity |   .0005615   .0002572     2.18   0.029     .0000571    .0010659
                    |
      c.year#c.laty |   .0753447   .0119883     6.28   0.000     .0518336    .0988557
                    |
      c.year#c.lony |    .046616   .0089964     5.18   0.000     .0289725    .0642594
                    |
              yprcp |   .0003864   .0003102     1.25   0.213     -.000222    .0009948
               ytav |   .2897727   .1774837     1.63   0.103    -.0583031    .6378484
             ydda29 |  -.0022905   .0026778    -0.86   0.392    -.0075422    .0029611
             yddb10 |   .0001757    .000744     0.24   0.813    -.0012834    .0016348
                    |
 c.year#c.lnpop1940 |  -.5755314   .1470365    -3.91   0.000     -.863895   -.2871679
                    |
 c.year#c.lnemp1940 |   .7089871   .1455645     4.87   0.000     .4235102    .9944639
                    |
 c.year#c.lnmfg1940 |  -.0345349   .0238395    -1.45   0.148    -.0812881    .0122184
                    |
 c.year#c.railroads |  -.0002037   .0001857    -1.10   0.273    -.0005679    .0001605
                    |
  c.year#c.inst1944 |   .0238913   .0303636     0.79   0.431     -.035657    .0834396
                    |
 c.year#c.light1940 |  -.9445971   .1485231    -6.36   0.000    -1.235876    -.653318
                    |
    cap30mile_hydro |   .0009463   .0543505     0.02   0.986    -.1056442    .1075367
               post |  -.3715711   .1172936    -3.17   0.002    -.6016037   -.1415385
        treat40post |   .3977796   .1673669     2.38   0.018     .0695446    .7260147
              _cons |   2521.817    1703.08     1.48   0.139    -818.2129    5861.847
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treat40post) nocons /*
> */ ctitle(ATA5_PA_c6) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Log infant mortality rate
. capture gen lnimr = ln(imr)

. reghdfe lnimr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167159389
Absorbing 2 HDFE groups                           F(  17,   1968) =      13.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6397
                                                  Adj R-squared   =     0.6396
                                                  Within R-sq.    =     0.0309
Number of clusters (county_fips) =      1,969     Root MSE        =     0.1913

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
              lnimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -6.00e-06   .0000102    -0.59   0.558    -.0000261    .0000141
                    |
          ccapacity |   .0000177   8.24e-06     2.15   0.032     1.52e-06    .0000338
                    |
      c.year#c.laty |   .0019802   .0003416     5.80   0.000     .0013101    .0026502
                    |
      c.year#c.lony |   .0013734   .0002542     5.40   0.000      .000875    .0018719
                    |
              yprcp |   .0000144   9.80e-06     1.47   0.143    -4.85e-06    .0000336
               ytav |   .0073318   .0050164     1.46   0.144    -.0025062    .0171698
             ydda29 |   -.000031   .0000839    -0.37   0.711    -.0001955    .0001334
             yddb10 |   2.02e-06   .0000225     0.09   0.928     -.000042    .0000461
                    |
 c.year#c.lnpop1940 |  -.0134897   .0039963    -3.38   0.001    -.0213271   -.0056523
                    |
 c.year#c.lnemp1940 |   .0183517   .0040177     4.57   0.000     .0104723    .0262312
                    |
 c.year#c.lnmfg1940 |  -.0012461   .0007299    -1.71   0.088    -.0026777    .0001854
                    |
 c.year#c.railroads |  -7.57e-06   5.60e-06    -1.35   0.176    -.0000185    3.41e-06
                    |
  c.year#c.inst1944 |  -.0000692   .0008129    -0.09   0.932    -.0016634    .0015251
                    |
 c.year#c.light1940 |  -.0239849   .0044865    -5.35   0.000    -.0327837   -.0151861
                    |
    cap30mile_hydro |   .0006521   .0015375     0.42   0.672    -.0023632    .0036675
               post |  -.0118371   .0036491    -3.24   0.001    -.0189936   -.0046806
          treatpost |   .0163109   .0057587     2.83   0.005      .005017    .0276047
              _cons |   67.60812   47.68533     1.42   0.156    -25.91092    161.1272
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(ATA5_PA_c7) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Effects by plant size
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post btreatpost streatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      15.70
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6786
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0364
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7746

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0001525   .0003649    -0.42   0.676     -.000868    .0005631
                    |
          ccapacity |   .0003904   .0002486     1.57   0.116    -.0000971     .000878
                    |
      c.year#c.laty |   .0759921   .0119361     6.37   0.000     .0525833    .0994009
                    |
      c.year#c.lony |   .0466514    .008945     5.22   0.000     .0291087    .0641941
                    |
              yprcp |    .000393    .000311     1.26   0.206    -.0002168    .0010029
               ytav |   .2907387     .17719     1.64   0.101     -.056761    .6382385
             ydda29 |  -.0021488    .002631    -0.82   0.414    -.0073087    .0030111
             yddb10 |   .0001793   .0007438     0.24   0.809    -.0012794     .001638
                    |
 c.year#c.lnpop1940 |  -.5704496   .1461518    -3.90   0.000    -.8570781   -.2838211
                    |
 c.year#c.lnemp1940 |   .7016259   .1447414     4.85   0.000     .4177635    .9854884
                    |
 c.year#c.lnmfg1940 |  -.0340268   .0237078    -1.44   0.151    -.0805219    .0124682
                    |
 c.year#c.railroads |  -.0002055    .000185    -1.11   0.267    -.0005684    .0001574
                    |
  c.year#c.inst1944 |   .0236748   .0301154     0.79   0.432    -.0353867    .0827363
                    |
 c.year#c.light1940 |   -.946561   .1473916    -6.42   0.000    -1.235621    -.657501
                    |
    cap30mile_hydro |   .0085977   .0542368     0.16   0.874    -.0977699    .1149654
               post |  -.4035313   .1198839    -3.37   0.001     -.638644   -.1684187
         btreatpost |    .754099   .2129487     3.54   0.000     .3364703    1.171728
         streatpost |   .1213518   .2527395     0.48   0.631    -.3743133    .6170169
              _cons |   2497.181   1692.997     1.48   0.140    -823.0737    5817.435
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(btreatpost streatpost) nocons /*
> */ ctitle(ATA5_PA_c8) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Effects by wind direction
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treatdown_post treatup_post /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      14.60
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6786
                                                  Adj R-squared   =     0.6785
                                                  Within R-sq.    =     0.0363
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7749

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0002177    .000369    -0.59   0.555    -.0009414    .0005059
                    |
          ccapacity |   .0005479   .0002536     2.16   0.031     .0000505    .0010453
                    |
      c.year#c.laty |   .0763693    .011918     6.41   0.000     .0529961    .0997426
                    |
      c.year#c.lony |    .046888   .0089711     5.23   0.000     .0292941    .0644818
                    |
              yprcp |   .0003898   .0003104     1.26   0.209    -.0002188    .0009985
               ytav |   .2903475   .1774292     1.64   0.102    -.0576214    .6383164
             ydda29 |  -.0022074   .0026624    -0.83   0.407    -.0074288     .003014
             yddb10 |   .0001788   .0007427     0.24   0.810    -.0012778    .0016355
                    |
 c.year#c.lnpop1940 |  -.5752609    .146299    -3.93   0.000    -.8621782   -.2883436
                    |
 c.year#c.lnemp1940 |   .7075641   .1449282     4.88   0.000     .4233352     .991793
                    |
 c.year#c.lnmfg1940 |  -.0339632   .0236623    -1.44   0.151    -.0803691    .0124427
                    |
 c.year#c.railroads |  -.0002007   .0001844    -1.09   0.277    -.0005623     .000161
                    |
  c.year#c.inst1944 |   .0239665    .030122     0.80   0.426    -.0351079    .0830408
                    |
 c.year#c.light1940 |  -.9503508   .1477464    -6.43   0.000    -1.240107    -.660595
                    |
    cap30mile_hydro |    .003791   .0538462     0.07   0.944    -.1018106    .1093926
               post |  -.4272366    .115867    -3.69   0.000    -.6544714   -.2000018
     treatdown_post |   .9446101   .3266081     2.89   0.004     .3040761    1.585144
       treatup_post |   .4921175   .2045029     2.41   0.016     .0910526    .8931825
              _cons |   2502.259   1693.966     1.48   0.140    -819.8957    5824.414
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatdown_post treatup_post) nocons /*
> */ ctitle(ATA5_PA_c9) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL B
. ****************************************
. *Baseline estimates
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post sc40treatpost bc40treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      16.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6787
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0366
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7740

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0003213   .0003799    -0.85   0.398    -.0010664    .0004238
                    |
          ccapacity |   .0004751   .0002552     1.86   0.063    -.0000254    .0009756
                    |
      c.year#c.laty |   .0761937   .0118799     6.41   0.000     .0528952    .0994923
                    |
      c.year#c.lony |   .0455851   .0089461     5.10   0.000     .0280403    .0631299
                    |
              yprcp |   .0003871   .0003112     1.24   0.214    -.0002233    .0009975
               ytav |   .2982854   .1773849     1.68   0.093    -.0495965    .6461673
             ydda29 |  -.0022396   .0026642    -0.84   0.401    -.0074645    .0029853
             yddb10 |   .0002131   .0007441     0.29   0.775    -.0012462    .0016724
                    |
 c.year#c.lnpop1940 |  -.5710179   .1453376    -3.93   0.000    -.8560497    -.285986
                    |
 c.year#c.lnemp1940 |   .6976037    .143632     4.86   0.000     .4159169    .9792906
                    |
 c.year#c.lnmfg1940 |  -.0332069   .0235343    -1.41   0.158    -.0793617    .0129478
                    |
 c.year#c.railroads |  -.0002009   .0001843    -1.09   0.276    -.0005623    .0001605
                    |
  c.year#c.inst1944 |   .0232994   .0299765     0.78   0.437    -.0354896    .0820884
                    |
 c.year#c.light1940 |  -.9414366    .146933    -6.41   0.000    -1.229597   -.6532759
                    |
    cap30mile_hydro |   .0088659   .0537267     0.17   0.869    -.0965013    .1142332
               post |  -.4666041   .1242965    -3.75   0.000    -.7103707   -.2228375
      sc40treatpost |  -.1936537   .3189781    -0.61   0.544    -.8192241    .4319167
      bc40treatpost |   .8704382   .2364355     3.68   0.000      .406748    1.334128
              _cons |   2393.649   1687.905     1.42   0.156    -916.6193    5703.917
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(ATA5_PB_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Weight by females age 15-44
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post sc40treatpost bc40treatpost /*
> */ [fw=popf15_44], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 1652295469
Absorbing 2 HDFE groups                           F(  18,   1968) =      16.82
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6887
                                                  Adj R-squared   =     0.6887
                                                  Within R-sq.    =     0.0413
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8654

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0004682   .0004286    -1.09   0.275    -.0013087    .0003724
                    |
          ccapacity |   .0006334   .0002774     2.28   0.023     .0000894    .0011774
                    |
      c.year#c.laty |   .0786641   .0128731     6.11   0.000     .0534179    .1039104
                    |
      c.year#c.lony |   .0508762   .0100364     5.07   0.000     .0311931    .0705592
                    |
              yprcp |   .0003767   .0003443     1.09   0.274    -.0002984    .0010519
               ytav |   .3555041   .2010046     1.77   0.077    -.0387001    .7497083
             ydda29 |   -.003905   .0033202    -1.18   0.240    -.0104165    .0026065
             yddb10 |   .0001144   .0008217     0.14   0.889    -.0014971     .001726
                    |
 c.year#c.lnpop1940 |  -.6189459   .1640029    -3.77   0.000    -.9405835   -.2973083
                    |
 c.year#c.lnemp1940 |   .7414122   .1618619     4.58   0.000     .4239734    1.058851
                    |
 c.year#c.lnmfg1940 |  -.0372346   .0258112    -1.44   0.149    -.0878547    .0133855
                    |
 c.year#c.railroads |  -.0001441   .0002015    -0.72   0.475    -.0005392    .0002511
                    |
  c.year#c.inst1944 |    .018805   .0341219     0.55   0.582    -.0481138    .0857238
                    |
 c.year#c.light1940 |  -.9833548   .1631989    -6.03   0.000    -1.303416   -.6632939
                    |
    cap30mile_hydro |  -.0055991   .0658666    -0.09   0.932    -.1347748    .1235766
               post |  -.6027334   .1410911    -4.27   0.000     -.879437   -.3260298
      sc40treatpost |  -.3284432   .3477676    -0.94   0.345    -1.010475    .3535881
      bc40treatpost |   1.011844   .2637842     3.84   0.000     .4945181    1.529169
              _cons |   3357.192   1878.713     1.79   0.074    -327.2837    7041.667
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(ATA5_PB_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Omit counties -- Treated by multiple plants
. capture drop ncy

. bysort county_fips year: gen ncy = _n

. capture drop N

. bysort county_fips treat: gen N = _N

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post sc40treatpost bc40treatpost /*
> */ if ((treat==1 & N==25) | (treat==0 & ncy==1)) [fw=births_rs], /*
> */ absorb(county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 39,885,256
Absorbing 2 HDFE groups                           F(  18,   1753) =       8.34
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6505
                                                  Adj R-squared   =     0.6505
                                                  Within R-sq.    =     0.0200
Number of clusters (county_fips) =      1,754     Root MSE        =     6.6961

                               (Std. Err. adjusted for 1,754 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |   4.00e-07   1.81e-06     0.22   0.825    -3.15e-06    3.95e-06
                    |
          ccapacity |   .0001886   .0004166     0.45   0.651    -.0006285    .0010057
                    |
      c.year#c.laty |   .0492677   .0136301     3.61   0.000     .0225347    .0760006
                    |
      c.year#c.lony |   .0174076   .0079264     2.20   0.028     .0018613    .0329538
                    |
              yprcp |   .0002871    .000268     1.07   0.284    -.0002386    .0008127
               ytav |   .1042363   .1500424     0.69   0.487    -.1900445    .3985172
             ydda29 |  -.0005751   .0028507    -0.20   0.840    -.0061662    .0050161
             yddb10 |  -.0002905   .0006557    -0.44   0.658    -.0015764    .0009954
                    |
 c.year#c.lnpop1940 |  -.3443747   .1469561    -2.34   0.019    -.6326025    -.056147
                    |
 c.year#c.lnemp1940 |   .4244597   .1460967     2.91   0.004     .1379177    .7110017
                    |
 c.year#c.lnmfg1940 |  -.0097753    .019499    -0.50   0.616    -.0480191    .0284684
                    |
 c.year#c.railroads |  -.0005942   .0001916    -3.10   0.002      -.00097   -.0002184
                    |
  c.year#c.inst1944 |   .0439896   .0248862     1.77   0.077    -.0048201    .0927992
                    |
 c.year#c.light1940 |  -1.053833   .1145523    -9.20   0.000    -1.278507   -.8291599
                    |
    cap30mile_hydro |   .0373804   .0510587     0.73   0.464    -.0627621    .1375228
               post |  -.3022904   .1652642    -1.83   0.068    -.6264261    .0218453
      sc40treatpost |  -.0064305   .3545838    -0.02   0.986    -.7018821    .6890211
      bc40treatpost |   1.339153   .4095973     3.27   0.001     .5358026    2.142504
              _cons |   114.2685    1683.62     0.07   0.946    -3187.846    3416.383
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      1754        1754           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(ATA5_PB_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Omit counties -- 30-60 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post sc40treatpost bc40treatpost /*
> */ [fw=births_rs] if (dist_miles<=30 |dist_miles>=60), /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  133774415
Absorbing 2 HDFE groups                           F(  18,   1790) =      21.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6944
                                                  Adj R-squared   =     0.6944
                                                  Within R-sq.    =     0.0447
Number of clusters (county_fips) =      1,791     Root MSE        =     5.4123

                               (Std. Err. adjusted for 1,791 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0002905   .0004899    -0.59   0.553    -.0012514    .0006704
                    |
          ccapacity |   .0006821    .000288     2.37   0.018     .0001173    .0012469
                    |
      c.year#c.laty |   .0867396   .0121464     7.14   0.000     .0629171    .1105622
                    |
      c.year#c.lony |    .053645    .008701     6.17   0.000     .0365798    .0707102
                    |
              yprcp |   .0003073   .0003009     1.02   0.307    -.0002828    .0008974
               ytav |   .3624045   .1736514     2.09   0.037     .0218237    .7029854
             ydda29 |  -.0032127   .0025397    -1.26   0.206    -.0081939    .0017685
             yddb10 |   .0001571   .0007347     0.21   0.831    -.0012839    .0015982
                    |
 c.year#c.lnpop1940 |  -.4893221   .1431197    -3.42   0.001    -.7700213   -.2086228
                    |
 c.year#c.lnemp1940 |   .6449079   .1424314     4.53   0.000     .3655585    .9242572
                    |
 c.year#c.lnmfg1940 |  -.0556738   .0247589    -2.25   0.025    -.1042333   -.0071143
                    |
 c.year#c.railroads |  -.0002019   .0001564    -1.29   0.197    -.0005087    .0001048
                    |
  c.year#c.inst1944 |  -.0012466   .0297909    -0.04   0.967    -.0596751     .057182
                    |
 c.year#c.light1940 |  -.8444733   .1469391    -5.75   0.000    -1.132663   -.5562832
                    |
    cap30mile_hydro |   .0024486   .0623384     0.04   0.969    -.1198151    .1247122
               post |    -.53895   .1391736    -3.87   0.000    -.8119098   -.2659901
      sc40treatpost |  -.2836517   .3658359    -0.78   0.438    -1.001162    .4338586
      bc40treatpost |   .6942013   .2047017     3.39   0.001     .2927219    1.095681
              _cons |   2381.173   1691.579     1.41   0.159    -936.5041     5698.85
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      3657        3657           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(ATA5_PB_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Alternate treatment radii -- <20 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post bc40treat20post sc40treat20post /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      17.05
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6786
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0363
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7748

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0005457   .0004203    -1.30   0.194      -.00137    .0002786
                    |
          ccapacity |   .0004839   .0002544     1.90   0.057     -.000015    .0009828
                    |
      c.year#c.laty |   .0748723   .0119901     6.24   0.000     .0513577    .0983869
                    |
      c.year#c.lony |   .0464989   .0089752     5.18   0.000     .0288971    .0641008
                    |
              yprcp |   .0003905   .0003107     1.26   0.209    -.0002189    .0009999
               ytav |   .2912258   .1768964     1.65   0.100    -.0556983    .6381498
             ydda29 |  -.0022447   .0026799    -0.84   0.402    -.0075004     .003011
             yddb10 |   .0001771   .0007436     0.24   0.812    -.0012813    .0016354
                    |
 c.year#c.lnpop1940 |  -.5772153   .1463405    -3.94   0.000     -.864214   -.2902167
                    |
 c.year#c.lnemp1940 |   .7063302   .1448308     4.88   0.000     .4222924     .990368
                    |
 c.year#c.lnmfg1940 |  -.0338827   .0236899    -1.43   0.153    -.0803425    .0125772
                    |
 c.year#c.railroads |  -.0001943   .0001862    -1.04   0.297    -.0005594    .0001708
                    |
  c.year#c.inst1944 |   .0238827   .0302461     0.79   0.430     -.035435    .0832004
                    |
 c.year#c.light1940 |  -.9386849   .1483935    -6.33   0.000     -1.22971   -.6476599
                    |
    cap30mile_hydro |   .0026592   .0540855     0.05   0.961    -.1034117    .1087301
               post |  -.2424512   .1005114    -2.41   0.016    -.4395712   -.0453311
    bc40treat20post |   .5575331   .2365854     2.36   0.019     .0935489    1.021517
    sc40treat20post |  -.6457038   .4043698    -1.60   0.110    -1.438742    .1473342
              _cons |   2628.907   1691.479     1.55   0.120    -688.3708    5946.184
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(bc40treat20post sc40treat20post) nocons /*
> */ ctitle(ATA5_PB_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Alternate treatment radii -- <40 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post bc40treat40post sc40treat40post /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      16.89
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6786
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0365
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7742

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0004108   .0004441    -0.92   0.355    -.0012818    .0004602
                    |
          ccapacity |   .0004586   .0002569     1.79   0.074    -.0000452    .0009623
                    |
      c.year#c.laty |    .075807    .011897     6.37   0.000     .0524749    .0991391
                    |
      c.year#c.lony |   .0453206   .0089444     5.07   0.000     .0277791    .0628622
                    |
              yprcp |    .000385   .0003109     1.24   0.216    -.0002247    .0009946
               ytav |   .2958795   .1774281     1.67   0.096    -.0520872    .6438462
             ydda29 |  -.0023011   .0026561    -0.87   0.386    -.0075102     .002908
             yddb10 |   .0002107   .0007436     0.28   0.777    -.0012477    .0016691
                    |
 c.year#c.lnpop1940 |  -.5769113   .1461791    -3.95   0.000    -.8635934   -.2902292
                    |
 c.year#c.lnemp1940 |   .7041211   .1445797     4.87   0.000     .4205757    .9876666
                    |
 c.year#c.lnmfg1940 |   -.033313   .0235508    -1.41   0.157    -.0795002    .0128742
                    |
 c.year#c.railroads |  -.0001993   .0001851    -1.08   0.282    -.0005624    .0001638
                    |
  c.year#c.inst1944 |   .0231153   .0299955     0.77   0.441    -.0357109    .0819415
                    |
 c.year#c.light1940 |  -.9460914   .1474133    -6.42   0.000    -1.235194   -.6569888
                    |
    cap30mile_hydro |    .008137   .0540323     0.15   0.880    -.0978295    .1141036
               post |  -.4014208   .1193394    -3.36   0.001    -.6354656    -.167376
    bc40treat40post |   .7291926   .1972285     3.70   0.000     .3423938    1.115991
    sc40treat40post |  -.3049371   .2836986    -1.07   0.283    -.8613182     .251444
              _cons |   2395.257   1691.937     1.42   0.157     -922.919    5713.433
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(bc40treat40post sc40treat40post) nocons /*
> */ ctitle(ATA5_PB_c6) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Log infant mortality rate
. capture gen lnimr = ln(imr)

. reghdfe lnimr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post sc40treatpost bc40treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167159389
Absorbing 2 HDFE groups                           F(  18,   1968) =      14.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6397
                                                  Adj R-squared   =     0.6397
                                                  Within R-sq.    =     0.0311
Number of clusters (county_fips) =      1,969     Root MSE        =     0.1912

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
              lnimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -8.92e-06   .0000106    -0.84   0.400    -.0000297    .0000119
                    |
          ccapacity |   .0000158   8.20e-06     1.93   0.054    -2.48e-07    .0000319
                    |
      c.year#c.laty |   .0019902   .0003412     5.83   0.000     .0013209    .0026594
                    |
      c.year#c.lony |   .0013517    .000255     5.30   0.000     .0008516    .0018519
                    |
              yprcp |   .0000143   9.81e-06     1.46   0.145    -4.94e-06    .0000335
               ytav |   .0074969   .0050223     1.49   0.136    -.0023526    .0173464
             ydda29 |  -.0000311   .0000836    -0.37   0.710    -.0001951    .0001329
             yddb10 |   2.83e-06   .0000225     0.13   0.900    -.0000413    .0000469
                    |
 c.year#c.lnpop1940 |  -.0134266   .0039691    -3.38   0.001    -.0212107   -.0056425
                    |
 c.year#c.lnemp1940 |   .0181596   .0039819     4.56   0.000     .0103504    .0259688
                    |
 c.year#c.lnmfg1940 |  -.0012218   .0007248    -1.69   0.092    -.0026432    .0001996
                    |
 c.year#c.railroads |  -7.50e-06   5.60e-06    -1.34   0.180    -.0000185    3.48e-06
                    |
  c.year#c.inst1944 |  -.0000849   .0008085    -0.10   0.916    -.0016704    .0015007
                    |
 c.year#c.light1940 |  -.0238962   .0044725    -5.34   0.000    -.0326676   -.0151248
                    |
    cap30mile_hydro |   .0007471   .0015296     0.49   0.625    -.0022527    .0037469
               post |  -.0123527   .0037088    -3.33   0.001    -.0196263   -.0050792
      sc40treatpost |  -.0028113   .0093816    -0.30   0.764    -.0212101    .0155876
      bc40treatpost |   .0225325    .006915     3.26   0.001     .0089709     .036094
              _cons |   65.50792   47.75453     1.37   0.170    -28.14684    159.1627
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(ATA5_PB_c7) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL C
. ****************************************
. *Baseline estimates
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post ltreatpost htreatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      16.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6787
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0366
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7741

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0002947   .0003819    -0.77   0.440    -.0010436    .0004542
                    |
          ccapacity |   .0005045   .0002557     1.97   0.049     3.01e-06    .0010061
                    |
      c.year#c.laty |   .0732899    .012142     6.04   0.000     .0494774    .0971024
                    |
      c.year#c.lony |   .0464599   .0089062     5.22   0.000     .0289932    .0639265
                    |
              yprcp |   .0003821   .0003109     1.23   0.219    -.0002277    .0009919
               ytav |   .2935867   .1769993     1.66   0.097     -.053539    .6407124
             ydda29 |  -.0021973   .0026459    -0.83   0.406    -.0073863    .0029918
             yddb10 |   .0001864   .0007426     0.25   0.802    -.0012701    .0016429
                    |
 c.year#c.lnpop1940 |  -.5756784    .145617    -3.95   0.000    -.8612582   -.2900987
                    |
 c.year#c.lnemp1940 |    .701064   .1439289     4.87   0.000     .4187949    .9833331
                    |
 c.year#c.lnmfg1940 |  -.0347501   .0235858    -1.47   0.141    -.0810058    .0115057
                    |
 c.year#c.railroads |  -.0001723   .0001845    -0.93   0.350    -.0005342    .0001895
                    |
  c.year#c.inst1944 |   .0248975   .0298613     0.83   0.405    -.0336656    .0834606
                    |
 c.year#c.light1940 |  -.9268506   .1488133    -6.23   0.000    -1.218699   -.6350023
                    |
    cap30mile_hydro |   .0124342   .0536831     0.23   0.817    -.0928475     .117716
               post |  -.4641853   .1246653    -3.72   0.000    -.7086751   -.2196955
         ltreatpost |   .0179701    .290646     0.06   0.951    -.5520362    .5879763
         htreatpost |   .9355644   .2652811     3.53   0.000      .415303    1.455826
              _cons |   2786.014     1707.8     1.63   0.103    -563.2737    6135.301
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(ATA5_PC_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Weight by females age 15-44
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post ltreatpost htreatpost /*
> */ [fw=popf15_44], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 1652295469
Absorbing 2 HDFE groups                           F(  18,   1968) =      17.07
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6887
                                                  Adj R-squared   =     0.6887
                                                  Within R-sq.    =     0.0413
Number of clusters (county_fips) =      1,969     Root MSE        =     5.8657

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0004337   .0004304    -1.01   0.314    -.0012779    .0004104
                    |
          ccapacity |   .0006746   .0002786     2.42   0.016     .0001283    .0012209
                    |
      c.year#c.laty |   .0750181   .0132447     5.66   0.000     .0490431    .1009931
                    |
      c.year#c.lony |   .0519396   .0099976     5.20   0.000     .0323325    .0715466
                    |
              yprcp |   .0003677   .0003433     1.07   0.284    -.0003055     .001041
               ytav |   .3492589   .2007982     1.74   0.082    -.0445405    .7430584
             ydda29 |  -.0038803   .0032994    -1.18   0.240     -.010351    .0025903
             yddb10 |   .0000842   .0008204     0.10   0.918    -.0015247    .0016931
                    |
 c.year#c.lnpop1940 |  -.6245222   .1643601    -3.80   0.000    -.9468603   -.3021842
                    |
 c.year#c.lnemp1940 |   .7459399   .1623446     4.59   0.000     .4275545    1.064325
                    |
 c.year#c.lnmfg1940 |  -.0389882   .0258713    -1.51   0.132    -.0897262    .0117498
                    |
 c.year#c.railroads |  -.0001114   .0002023    -0.55   0.582    -.0005081    .0002853
                    |
  c.year#c.inst1944 |    .020641   .0340106     0.61   0.544    -.0460596    .0873416
                    |
 c.year#c.light1940 |  -.9669112   .1658039    -5.83   0.000    -1.292081   -.6417416
                    |
    cap30mile_hydro |  -.0009572   .0658676    -0.01   0.988    -.1301348    .1282204
               post |  -.5985634   .1415893    -4.23   0.000    -.8762442   -.3208827
         ltreatpost |  -.0117012   .3313523    -0.04   0.972    -.6615395    .6381371
         htreatpost |   1.064686   .2934716     3.63   0.000      .489138    1.640234
              _cons |   3834.267   1906.502     2.01   0.044     95.29204    7573.242
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(ATA5_PC_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Omit counties -- Treated by multiple plants
. capture drop ncy

. bysort county_fips year: gen ncy = _n

. capture drop N

. bysort county_fips treat: gen N = _N

. 
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post ltreatpost htreatpost /*
> */ if ((treat==1 & N==25) | (treat==0 & ncy==1)) [fw=births_rs], /*
> */ absorb(county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 39,885,256
Absorbing 2 HDFE groups                           F(  18,   1753) =       8.76
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6505
                                                  Adj R-squared   =     0.6504
                                                  Within R-sq.    =     0.0198
Number of clusters (county_fips) =      1,754     Root MSE        =     6.6969

                               (Std. Err. adjusted for 1,754 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |   4.17e-07   1.81e-06     0.23   0.818    -3.14e-06    3.97e-06
                    |
          ccapacity |   .0003092   .0004163     0.74   0.458    -.0005073    .0011257
                    |
      c.year#c.laty |   .0481815   .0135618     3.55   0.000     .0215824    .0747805
                    |
      c.year#c.lony |   .0186294   .0081072     2.30   0.022     .0027286    .0345302
                    |
              yprcp |   .0002988   .0002679     1.12   0.265    -.0002267    .0008242
               ytav |   .0993431   .1500897     0.66   0.508    -.1950305    .3937166
             ydda29 |  -.0006784   .0028524    -0.24   0.812    -.0062728     .004916
             yddb10 |  -.0003159    .000655    -0.48   0.630    -.0016005    .0009688
                    |
 c.year#c.lnpop1940 |  -.3492613   .1467272    -2.38   0.017      -.63704   -.0614825
                    |
 c.year#c.lnemp1940 |   .4305591   .1455656     2.96   0.003     .1450587    .7160594
                    |
 c.year#c.lnmfg1940 |   -.012357     .01971    -0.63   0.531    -.0510146    .0263006
                    |
 c.year#c.railroads |  -.0005761   .0001875    -3.07   0.002    -.0009438   -.0002084
                    |
  c.year#c.inst1944 |   .0457277   .0250757     1.82   0.068    -.0034537    .0949091
                    |
 c.year#c.light1940 |  -1.039705   .1142411    -9.10   0.000    -1.263768    -.815642
                    |
    cap30mile_hydro |   .0405348   .0506279     0.80   0.423    -.0587627    .1398323
               post |  -.3106149   .1651067    -1.88   0.060    -.6344415    .0132118
         ltreatpost |   .1548115   .3095214     0.50   0.617    -.4522585    .7618814
         htreatpost |   1.267389   .5060349     2.50   0.012     .2748935    2.259884
              _cons |   404.2993   1683.029     0.24   0.810    -2896.656    3705.255
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      1754        1754           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(ATA5_PC_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Omit counties -- 30-60 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post ltreatpost htreatpost /*
> */ [fw=births_rs] if (dist_miles<=30 |dist_miles>=60), /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  133774415
Absorbing 2 HDFE groups                           F(  18,   1790) =      21.21
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6944
                                                  Adj R-squared   =     0.6944
                                                  Within R-sq.    =     0.0446
Number of clusters (county_fips) =      1,791     Root MSE        =     5.4125

                               (Std. Err. adjusted for 1,791 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0002481   .0004915    -0.50   0.614    -.0012121     .000716
                    |
          ccapacity |   .0007164   .0002879     2.49   0.013     .0001517    .0012812
                    |
      c.year#c.laty |   .0836214   .0124032     6.74   0.000      .059295    .1079477
                    |
      c.year#c.lony |   .0547718   .0086473     6.33   0.000     .0378119    .0717317
                    |
              yprcp |    .000301   .0003002     1.00   0.316    -.0002877    .0008897
               ytav |   .3578435   .1730662     2.07   0.039     .0184105    .6972765
             ydda29 |  -.0031864   .0025227    -1.26   0.207    -.0081342    .0017613
             yddb10 |   .0001293    .000732     0.18   0.860    -.0013062    .0015649
                    |
 c.year#c.lnpop1940 |  -.4923558   .1430571    -3.44   0.001    -.7729323   -.2117792
                    |
 c.year#c.lnemp1940 |   .6472523   .1423616     4.55   0.000     .3680399    .9264648
                    |
 c.year#c.lnmfg1940 |  -.0571787   .0248106    -2.30   0.021    -.1058395    -.008518
                    |
 c.year#c.railroads |  -.0001738   .0001568    -1.11   0.268    -.0004813    .0001337
                    |
  c.year#c.inst1944 |   .0002768   .0296836     0.01   0.993    -.0579413    .0584948
                    |
 c.year#c.light1940 |  -.8311486   .1483245    -5.60   0.000    -1.122056   -.5402412
                    |
    cap30mile_hydro |   .0058018   .0630574     0.09   0.927    -.1178721    .1294757
               post |  -.5371249   .1395634    -3.85   0.000    -.8108493   -.2634005
         ltreatpost |  -.0371737   .3327238    -0.11   0.911    -.6897416    .6153942
         htreatpost |   .7345023   .2307851     3.18   0.001     .2818657    1.187139
              _cons |   2817.403   1712.774     1.64   0.100    -541.8429     6176.65
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      3657        3657           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(ATA5_PC_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Alternate treatment radii -- <20 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post htreat20post ltreat20post /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      17.34
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6786
                                                  Adj R-squared   =     0.6785
                                                  Within R-sq.    =     0.0363
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7749

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0005278   .0004199    -1.26   0.209    -.0013512    .0002957
                    |
          ccapacity |   .0004928   .0002558     1.93   0.054    -8.85e-06    .0009944
                    |
      c.year#c.laty |    .073274   .0121318     6.04   0.000     .0494815    .0970664
                    |
      c.year#c.lony |   .0470929   .0089571     5.26   0.000     .0295264    .0646593
                    |
              yprcp |   .0003863   .0003103     1.24   0.213    -.0002223    .0009949
               ytav |   .2912758    .176855     1.65   0.100    -.0555668    .6381185
             ydda29 |  -.0022704   .0026728    -0.85   0.396    -.0075122    .0029713
             yddb10 |   .0001703   .0007435     0.23   0.819    -.0012878    .0016285
                    |
 c.year#c.lnpop1940 |  -.5770969   .1465669    -3.94   0.000    -.8645395   -.2896543
                    |
 c.year#c.lnemp1940 |   .7059093   .1450429     4.87   0.000     .4214555    .9903632
                    |
 c.year#c.lnmfg1940 |  -.0349161   .0237328    -1.47   0.141    -.0814602    .0116279
                    |
 c.year#c.railroads |  -.0001841   .0001867    -0.99   0.324    -.0005503    .0001821
                    |
  c.year#c.inst1944 |   .0253563   .0302056     0.84   0.401    -.0338821    .0845947
                    |
 c.year#c.light1940 |    -.92996   .1496974    -6.21   0.000    -1.223542   -.6363779
                    |
    cap30mile_hydro |   .0053371   .0540378     0.10   0.921    -.1006402    .1113144
               post |   -.241106   .1007433    -2.39   0.017    -.4386808   -.0435312
       htreat20post |   .6071795    .261188     2.32   0.020     .0949454    1.119414
       ltreat20post |  -.3869933   .3371427    -1.15   0.251    -1.048188     .274201
              _cons |   2853.083   1699.888     1.68   0.093    -480.6869    6186.852
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(htreat20post ltreat20post) nocons /*
> */ ctitle(ATA5_PC_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Alternate treatment radii -- <40 miles from plant
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post htreat40post ltreat40post /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      17.57
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6786
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0365
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7741

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |   -.000423   .0004507    -0.94   0.348    -.0013069    .0004609
                    |
          ccapacity |    .000511   .0002592     1.97   0.049     2.70e-06    .0010193
                    |
      c.year#c.laty |   .0727966   .0121279     6.00   0.000     .0490118    .0965815
                    |
      c.year#c.lony |   .0466134   .0089394     5.21   0.000     .0290817     .064145
                    |
              yprcp |   .0003755   .0003104     1.21   0.226    -.0002331    .0009842
               ytav |     .29183   .1769525     1.65   0.099    -.0552041     .638864
             ydda29 |  -.0022627   .0026356    -0.86   0.391    -.0074315    .0029061
             yddb10 |   .0001864   .0007429     0.25   0.802    -.0012705    .0016433
                    |
 c.year#c.lnpop1940 |  -.5798338   .1462227    -3.97   0.000    -.8666013   -.2930663
                    |
 c.year#c.lnemp1940 |    .705522   .1446377     4.88   0.000     .4218629    .9891812
                    |
 c.year#c.lnmfg1940 |  -.0352136   .0236111    -1.49   0.136     -.081519    .0110917
                    |
 c.year#c.railroads |  -.0001715   .0001856    -0.92   0.356    -.0005356    .0001926
                    |
  c.year#c.inst1944 |   .0248382   .0299872     0.83   0.408    -.0339717    .0836481
                    |
 c.year#c.light1940 |  -.9283951   .1487156    -6.24   0.000    -1.220052   -.6367385
                    |
    cap30mile_hydro |   .0086253   .0535319     0.16   0.872    -.0963599    .1136105
               post |  -.4014891   .1195633    -3.36   0.001    -.6359731   -.1670051
       htreat40post |     .79706   .2200678     3.62   0.000     .3654697     1.22865
       ltreat40post |  -.2088503   .2792268    -0.75   0.455    -.7564616     .338761
              _cons |    2872.51   1720.019     1.67   0.095    -500.7388    6245.759
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(htreat40post ltreat40post) nocons /*
> */ ctitle(ATA5_PC_c6) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *Log infant mortality rate
. capture gen lnimr = ln(imr)

. reghdfe lnimr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post ltreatpost htreatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167159389
Absorbing 2 HDFE groups                           F(  18,   1968) =      14.32
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6397
                                                  Adj R-squared   =     0.6397
                                                  Within R-sq.    =     0.0311
Number of clusters (county_fips) =      1,969     Root MSE        =     0.1912

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
              lnimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -8.12e-06   .0000107    -0.76   0.447    -.0000291    .0000128
                    |
          ccapacity |   .0000166   8.20e-06     2.03   0.043     5.26e-07    .0000327
                    |
      c.year#c.laty |   .0019251   .0003433     5.61   0.000     .0012518    .0025984
                    |
      c.year#c.lony |   .0013727   .0002543     5.40   0.000     .0008741    .0018713
                    |
              yprcp |   .0000142   9.80e-06     1.45   0.148    -5.03e-06    .0000334
               ytav |   .0073809   .0050096     1.47   0.141    -.0024438    .0172056
             ydda29 |  -.0000302   .0000835    -0.36   0.718    -.0001939    .0001335
             yddb10 |   2.18e-06   .0000224     0.10   0.923    -.0000418    .0000462
                    |
 c.year#c.lnpop1940 |  -.0135335   .0039848    -3.40   0.001    -.0213483   -.0057187
                    |
 c.year#c.lnemp1940 |   .0182487   .0039924     4.57   0.000     .0104189    .0260784
                    |
 c.year#c.lnmfg1940 |  -.0012575    .000727    -1.73   0.084    -.0026833    .0001683
                    |
 c.year#c.railroads |  -6.88e-06   5.64e-06    -1.22   0.223    -.0000179    4.18e-06
                    |
  c.year#c.inst1944 |  -.0000483   .0008073    -0.06   0.952    -.0016315    .0015349
                    |
 c.year#c.light1940 |  -.0235782   .0045451    -5.19   0.000    -.0324919   -.0146646
                    |
    cap30mile_hydro |   .0008196   .0015354     0.53   0.594    -.0021916    .0038307
               post |  -.0122636   .0037189    -3.30   0.001     -.019557   -.0049702
         ltreatpost |   .0032075   .0086491     0.37   0.711    -.0137549    .0201699
         htreatpost |   .0235447   .0077207     3.05   0.002      .008403    .0386864
              _cons |   74.35902   48.31217     1.54   0.124    -20.38935    169.1074
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(ATA5_PC_c7) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX TABLE A.6
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/eventstudy_treat30miles_90_11_7.dta, clear

. 
. global Geot1 c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. 
. global Econt1 c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. 
. global Econnlnt1 c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. ****************************************
. ***PANEL A
. ****************************************
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  17,   1968) =      15.46
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6785
                                                  Adj R-squared   =     0.6785
                                                  Within R-sq.    =     0.0362
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7751

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0001989   .0003662    -0.54   0.587    -.0009171    .0005193
                    |
          ccapacity |   .0005522   .0002555     2.16   0.031     .0000512    .0010532
                    |
      c.year#c.laty |    .075773   .0119439     6.34   0.000     .0523491     .099197
                    |
      c.year#c.lony |   .0464917   .0089661     5.19   0.000     .0289076    .0640757
                    |
              yprcp |   .0003901   .0003106     1.26   0.209    -.0002191    .0009992
               ytav |   .2914035   .1773787     1.64   0.101    -.0564663    .6392733
             ydda29 |  -.0022367   .0026736    -0.84   0.403    -.0074801    .0030067
             yddb10 |   .0001793   .0007433     0.24   0.809    -.0012784    .0016369
                    |
 c.year#c.lnpop1940 |  -.5737178   .1465213    -3.92   0.000    -.8610709   -.2863646
                    |
 c.year#c.lnemp1940 |   .7057342    .145045     4.87   0.000     .4212763    .9901921
                    |
 c.year#c.lnmfg1940 |  -.0342414   .0237608    -1.44   0.150    -.0808403    .0123575
                    |
 c.year#c.railroads |  -.0002035   .0001848    -1.10   0.271     -.000566     .000159
                    |
  c.year#c.inst1944 |   .0239572    .030214     0.79   0.428    -.0352976     .083212
                    |
 c.year#c.light1940 |  -.9451938    .147773    -6.40   0.000    -1.235002   -.6553858
                    |
    cap30mile_hydro |   .0048784   .0541433     0.09   0.928    -.1013059    .1110626
               post |  -.4449091   .1217639    -3.65   0.000    -.6837089   -.2061094
          treatpost |   .6090359   .1915582     3.18   0.001     .2333576    .9847142
              _cons |   2481.377   1693.956     1.46   0.143    -840.7585    5803.512
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. local r2_oster = `e(r2)'*1.3

. di `r2_oster'
.88210013

. psacalc2 beta treatpost, rmax(`r2_oster')

                 ---- Treatment Effect Estimate ----
             |     Estimate           Sq. difference      Bias changes
             |                      from controlled beta    direction
-------------+----------------------------------------------------------------
Beta         |      14.18899                  184             
Alt. sol. 1  |     -99.17576                    0             Yes
Alt. sol. 2  |                                                
-------------+----------------------------------------------------------------

                 ---- Inputs from Regressions ----
             |      Coeff.            R-Squared
-------------+----------------------------------------------------------------
Uncontrolled |       -5.56068         0.054
Controlled   |        0.60904         0.679
-------------+----------------------------------------------------------------

                 ---- Other Inputs ----
-------------+----------------------------------------------------------------
R_max        |   0.882
Delta        |   1.000
Unr. Controls|   
-------------+----------------------------------------------------------------

. local beta1 = r(beta)

. psacalc2 delta treatpost, rmax(`r2_oster')

                 ---- Bound Estimate ----
-------------+----------------------------------------------------------------
delta        |      -0.11109
-------------+----------------------------------------------------------------

                 ---- Inputs from Regressions ----
             |      Coeff.                      R-Squared
-------------+----------------------------------------------------------------
Uncontrolled |       -5.56068                   0.054
Controlled   |        0.60904                   0.679
-------------+----------------------------------------------------------------

                 ---- Other Inputs ----
-------------+----------------------------------------------------------------
R_max        |   0.882
Beta         |    0.000000
Unr. Controls|   
-------------+----------------------------------------------------------------

. local delta1 = r(delta)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(treatpost) nocons /*
> */ ctitle(ATA6_PA) se bdec(3) sdec(3) rdec(3) /*
> */ addstat("r2_oster", `r2_oster', "delta1", `delta1', "beta1", `beta1') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL B
. ****************************************
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post sc40treatpost bc40treatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      16.42
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6787
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0366
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7740

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0003213   .0003799    -0.85   0.398    -.0010664    .0004238
                    |
          ccapacity |   .0004751   .0002552     1.86   0.063    -.0000254    .0009756
                    |
      c.year#c.laty |   .0761937   .0118799     6.41   0.000     .0528952    .0994923
                    |
      c.year#c.lony |   .0455851   .0089461     5.10   0.000     .0280403    .0631299
                    |
              yprcp |   .0003871   .0003112     1.24   0.214    -.0002233    .0009975
               ytav |   .2982854   .1773849     1.68   0.093    -.0495965    .6461673
             ydda29 |  -.0022396   .0026642    -0.84   0.401    -.0074645    .0029853
             yddb10 |   .0002131   .0007441     0.29   0.775    -.0012462    .0016724
                    |
 c.year#c.lnpop1940 |  -.5710179   .1453376    -3.93   0.000    -.8560497    -.285986
                    |
 c.year#c.lnemp1940 |   .6976037    .143632     4.86   0.000     .4159169    .9792906
                    |
 c.year#c.lnmfg1940 |  -.0332069   .0235343    -1.41   0.158    -.0793617    .0129478
                    |
 c.year#c.railroads |  -.0002009   .0001843    -1.09   0.276    -.0005623    .0001605
                    |
  c.year#c.inst1944 |   .0232994   .0299765     0.78   0.437    -.0354896    .0820884
                    |
 c.year#c.light1940 |  -.9414366    .146933    -6.41   0.000    -1.229597   -.6532759
                    |
    cap30mile_hydro |   .0088659   .0537267     0.17   0.869    -.0965013    .1142332
               post |  -.4666041   .1242965    -3.75   0.000    -.7103707   -.2228375
      sc40treatpost |  -.1936537   .3189781    -0.61   0.544    -.8192241    .4319167
      bc40treatpost |   .8704382   .2364355     3.68   0.000      .406748    1.334128
              _cons |   2393.649   1687.905     1.42   0.156    -916.6193    5703.917
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. local r2_oster = `e(r2)'*1.3

. di `r2_oster'
.88225772

. psacalc2 beta bc40treatpost, rmax(`r2_oster')

                 ---- Treatment Effect Estimate ----
             |     Estimate           Sq. difference      Bias changes
             |                      from controlled beta    direction
-------------+----------------------------------------------------------------
Beta         |       5.97107                   26             
Alt. sol. 1  |    -357.99979                    0             Yes
Alt. sol. 2  |                                                
-------------+----------------------------------------------------------------

                 ---- Inputs from Regressions ----
             |      Coeff.            R-Squared
-------------+----------------------------------------------------------------
Uncontrolled |       -5.57662         0.047
Controlled   |        0.87044         0.679
-------------+----------------------------------------------------------------

                 ---- Other Inputs ----
-------------+----------------------------------------------------------------
R_max        |   0.882
Delta        |   1.000
Unr. Controls|   
-------------+----------------------------------------------------------------

. local beta1 = r(beta)

. psacalc2 delta bc40treatpost, rmax(`r2_oster')

                 ---- Bound Estimate ----
-------------+----------------------------------------------------------------
delta        |      -0.24431
-------------+----------------------------------------------------------------

                 ---- Inputs from Regressions ----
             |      Coeff.                      R-Squared
-------------+----------------------------------------------------------------
Uncontrolled |       -5.57662                   0.047
Controlled   |        0.87044                   0.679
-------------+----------------------------------------------------------------

                 ---- Other Inputs ----
-------------+----------------------------------------------------------------
R_max        |   0.882
Beta         |    0.000000
Unr. Controls|   
-------------+----------------------------------------------------------------

. local delta1 = r(delta)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(sc40treatpost bc40treatpost) nocons /*
> */ ctitle(ATA6_PB_c3) se bdec(3) sdec(3) rdec(3) /*
> */ addstat("r2_oster", `r2_oster', "beta1", `beta1', "delta1", `delta1') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL C
. ****************************************
. reghdfe imr /*
> */ c.year#c.dist_miles ccapacity /*
> */ $Geot1 $Econt1 /*
> */ c.year#c.light1940 cap30mile_hydro /*
> */ post ltreatpost htreatpost /*
> */ [fw=births_rs], /*
> */ absorb(idcountyplant i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   =  167256513
Absorbing 2 HDFE groups                           F(  18,   1968) =      16.86
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6787
                                                  Adj R-squared   =     0.6786
                                                  Within R-sq.    =     0.0366
Number of clusters (county_fips) =      1,969     Root MSE        =     5.7741

                               (Std. Err. adjusted for 1,969 clusters in county_fips)
-------------------------------------------------------------------------------------
                    |               Robust
                imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
--------------------+----------------------------------------------------------------
c.year#c.dist_miles |  -.0002947   .0003819    -0.77   0.440    -.0010436    .0004542
                    |
          ccapacity |   .0005045   .0002557     1.97   0.049     3.01e-06    .0010061
                    |
      c.year#c.laty |   .0732899    .012142     6.04   0.000     .0494774    .0971024
                    |
      c.year#c.lony |   .0464599   .0089062     5.22   0.000     .0289932    .0639265
                    |
              yprcp |   .0003821   .0003109     1.23   0.219    -.0002277    .0009919
               ytav |   .2935867   .1769993     1.66   0.097     -.053539    .6407124
             ydda29 |  -.0021973   .0026459    -0.83   0.406    -.0073863    .0029918
             yddb10 |   .0001864   .0007426     0.25   0.802    -.0012701    .0016429
                    |
 c.year#c.lnpop1940 |  -.5756784    .145617    -3.95   0.000    -.8612582   -.2900987
                    |
 c.year#c.lnemp1940 |    .701064   .1439289     4.87   0.000     .4187949    .9833331
                    |
 c.year#c.lnmfg1940 |  -.0347501   .0235858    -1.47   0.141    -.0810058    .0115057
                    |
 c.year#c.railroads |  -.0001723   .0001845    -0.93   0.350    -.0005342    .0001895
                    |
  c.year#c.inst1944 |   .0248975   .0298613     0.83   0.405    -.0336656    .0834606
                    |
 c.year#c.light1940 |  -.9268506   .1488133    -6.23   0.000    -1.218699   -.6350023
                    |
    cap30mile_hydro |   .0124342   .0536831     0.23   0.817    -.0928475     .117716
               post |  -.4641853   .1246653    -3.72   0.000    -.7086751   -.2196955
         ltreatpost |   .0179701    .290646     0.06   0.951    -.5520362    .5879763
         htreatpost |   .9355644   .2652811     3.53   0.000      .415303    1.455826
              _cons |   2786.014     1707.8     1.63   0.103    -563.2737    6135.301
-------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
     idcountyplant |      5280        5280           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. local r2_oster = `e(r2)'*1.3

. di `r2_oster'
.88225

. psacalc2 beta htreatpost, rmax(`r2_oster')

                 ---- Treatment Effect Estimate ----
             |     Estimate           Sq. difference      Bias changes
             |                      from controlled beta    direction
-------------+----------------------------------------------------------------
Beta         |       4.03005                 9.58             
Alt. sol. 1  |    -721.01060                    0             Yes
Alt. sol. 2  |                                                
-------------+----------------------------------------------------------------

                 ---- Inputs from Regressions ----
             |      Coeff.            R-Squared
-------------+----------------------------------------------------------------
Uncontrolled |       -5.90357         0.047
Controlled   |        0.93556         0.679
-------------+----------------------------------------------------------------

                 ---- Other Inputs ----
-------------+----------------------------------------------------------------
R_max        |   0.882
Delta        |   1.000
Unr. Controls|   
-------------+----------------------------------------------------------------

. local beta1 = r(beta)

. psacalc2 delta htreatpost, rmax(`r2_oster')

                 ---- Bound Estimate ----
-------------+----------------------------------------------------------------
delta        |      -0.34147
-------------+----------------------------------------------------------------

                 ---- Inputs from Regressions ----
             |      Coeff.                      R-Squared
-------------+----------------------------------------------------------------
Uncontrolled |       -5.90357                   0.047
Controlled   |        0.93556                   0.679
-------------+----------------------------------------------------------------

                 ---- Other Inputs ----
-------------+----------------------------------------------------------------
R_max        |   0.882
Beta         |    0.000000
Unr. Controls|   
-------------+----------------------------------------------------------------

. local delta1 = r(delta)

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ltreatpost htreatpost) nocons /*
> */ ctitle(ATA6_PC) se bdec(3) sdec(3) rdec(3) /*
> */ addstat("r2_oster", `r2_oster', "beta1", `beta1', "delta1", `delta1') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX TABLE A.7
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. xtset state_fips
       panel variable:  state_fips (unbalanced)

. 
. ****************************************
. ***PANEL A
. ****************************************
. *log(total employment)
. xtreg dcap30mile62_38 lnemp if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.1526                                         min =          1
     between = 0.2397                                         avg =       12.0
     overall = 0.1979                                         max =         38

                                                F(1,35)           =      15.63
corr(u_i, Xb)  = 0.1502                         Prob > F          =     0.0004

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       lnemp |    2.76516   .6993689     3.95   0.000     1.345365    4.184954
       _cons |  -20.01869   6.792099    -2.95   0.006    -33.80738   -6.229995
-------------+----------------------------------------------------------------
     sigma_u |  4.7056653
     sigma_e |  7.1295436
         rho |  .30344209   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(lnemp) nocons /*
> */ ctitle(ATA7_PA_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 lnemp if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0069                                         min =          2
     between = 0.4093                                         avg =       39.9
     overall = 0.0271                                         max =        124

                                                F(1,39)           =       9.42
corr(u_i, Xb)  = 0.2402                         Prob > F          =     0.0039

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       lnemp |   .3060869    .099706     3.07   0.004     .1044126    .5077612
       _cons |  -1.637115   .8719106    -1.88   0.068     -3.40072    .1264906
-------------+----------------------------------------------------------------
     sigma_u |  1.1991128
     sigma_e |  2.5286894
         rho |  .18358598   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(lnemp) nocons /*
> */ ctitle(ATA7_PA_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dlnemp if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0090                                         min =          1
     between = 0.0730                                         avg =       12.0
     overall = 0.0080                                         max =         38

                                                F(1,35)           =       2.47
corr(u_i, Xb)  = 0.0076                         Prob > F          =     0.1252

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dlnemp |   3.096514    1.97096     1.57   0.125     -.904748    7.097775
       _cons |   6.929627   .0596825   116.11   0.000     6.808465    7.050789
-------------+----------------------------------------------------------------
     sigma_u |  5.3021375
     sigma_e |  7.7102391
         rho |  .32106576   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dlnemp) nocons /*
> */ ctitle(ATA7_PA_c3) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dlnemp if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0019                                         min =          2
     between = 0.0493                                         avg =       39.9
     overall = 0.0058                                         max =        124

                                                F(1,39)           =       3.91
corr(u_i, Xb)  = 0.0954                         Prob > F          =     0.0550

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      dlnemp |   .5720077   .2891803     1.98   0.055    -.0129147     1.15693
       _cons |   1.078404   .0196382    54.91   0.000     1.038682    1.118126
-------------+----------------------------------------------------------------
     sigma_u |  1.2822385
     sigma_e |  2.5351152
         rho |  .20371042   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dlnemp) nocons /*
> */ ctitle(ATA7_PA_c4) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *manufacturing employment percentage
. xtreg dcap30mile62_38 pmfg if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0264                                         min =          1
     between = 0.0178                                         avg =       12.0
     overall = 0.0480                                         max =         38

                                                F(1,35)           =       4.52
corr(u_i, Xb)  = 0.1056                         Prob > F          =     0.0407

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        pmfg |   .0996222   .0468685     2.13   0.041      .004474    .1947703
       _cons |   4.522159   1.088511     4.15   0.000     2.312364    6.731954
-------------+----------------------------------------------------------------
     sigma_u |  5.3572574
     sigma_e |  7.6420937
         rho |  .32950187   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(pmfg) nocons /*
> */ ctitle(ATA7_PA_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 pmfg if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0020                                         min =          2
     between = 0.0588                                         avg =       39.9
     overall = 0.0201                                         max =        124

                                                F(1,39)           =       1.04
corr(u_i, Xb)  = 0.2733                         Prob > F          =     0.3136

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        pmfg |   .0134337   .0131596     1.02   0.314     -.013184    .0400514
       _cons |   .8929273   .1436396     6.22   0.000     .6023888    1.183466
-------------+----------------------------------------------------------------
     sigma_u |  1.2748808
     sigma_e |  2.5349787
         rho |  .20186717   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(pmfg) nocons /*
> */ ctitle(ATA7_PA_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dpmfg if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0051                                         min =          1
     between = 0.0012                                         avg =       12.0
     overall = 0.0085                                         max =         38

                                                F(1,35)           =       2.09
corr(u_i, Xb)  = 0.0497                         Prob > F          =     0.1571

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       dpmfg |    .105446   .0729233     1.45   0.157    -.0425962    .2534882
       _cons |   6.590295    .169827    38.81   0.000     6.245528    6.935062
-------------+----------------------------------------------------------------
     sigma_u |  5.3942245
     sigma_e |  7.7252909
         rho |  .32775835   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dpmfg) nocons /*
> */ ctitle(ATA7_PA_c3) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dpmfg if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0002                                         min =          2
     between = 0.1303                                         avg =       39.9
     overall = 0.0041                                         max =        124

                                                F(1,39)           =       0.32
corr(u_i, Xb)  = 0.1463                         Prob > F          =     0.5731

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       dpmfg |   .0071471   .0125751     0.57   0.573    -.0182884    .0325825
       _cons |   1.031705   .0138201    74.65   0.000     1.003751    1.059659
-------------+----------------------------------------------------------------
     sigma_u |  1.2916137
     sigma_e |  2.5372136
         rho |  .20581345   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dpmfg) nocons /*
> */ ctitle(ATA7_PA_c4) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *manufacturing payroll per worker
. xtreg dcap30mile62_38 mfgwages_bls90 if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        417
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0306                                         min =          1
     between = 0.2221                                         avg =       11.6
     overall = 0.0694                                         max =         38

                                                F(1,35)           =       4.81
corr(u_i, Xb)  = 0.1681                         Prob > F          =     0.0351

                              (Std. Err. adjusted for 36 clusters in state_fips)
--------------------------------------------------------------------------------
               |               Robust
dcap30mile6~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
mfgwages_bls90 |    .431809   .1969732     2.19   0.035     .0319322    .8316858
         _cons |   3.299247   1.643501     2.01   0.052    -.0372377    6.635731
---------------+----------------------------------------------------------------
       sigma_u |  4.9393587
       sigma_e |  7.6757577
           rho |  .29283328   (fraction of variance due to u_i)
--------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(mfgwages_bls90) nocons /*
> */ ctitle(ATA7_PA_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 mfgwages_bls90 if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,442
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0000                                         min =          2
     between = 0.0380                                         avg =       36.0
     overall = 0.0000                                         max =        103

                                                F(1,39)           =       0.02
corr(u_i, Xb)  = 0.0050                         Prob > F          =     0.8753

                              (Std. Err. adjusted for 40 clusters in state_fips)
--------------------------------------------------------------------------------
               |               Robust
dcap30mile6~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
mfgwages_bls90 |  -.0001782   .0011278    -0.16   0.875    -.0024593     .002103
         _cons |   1.086969   .0080751   134.61   0.000     1.070636    1.103303
---------------+----------------------------------------------------------------
       sigma_u |  1.3111574
       sigma_e |  2.5769065
           rho |  .20564832   (fraction of variance due to u_i)
--------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(mfgwages_bls90) nocons /*
> */ ctitle(ATA7_PA_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dmfgwages_bls90 if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        400
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0005                                         min =          1
     between = 0.0349                                         avg =       11.1
     overall = 0.0005                                         max =         37

                                                F(1,35)           =       0.08
corr(u_i, Xb)  = 0.0048                         Prob > F          =     0.7739

                               (Std. Err. adjusted for 36 clusters in state_fips)
---------------------------------------------------------------------------------
                |               Robust
dcap30mile62_38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
dmfgwages_bls90 |   .0664341   .2295237     0.29   0.774    -.3995237     .532392
          _cons |   7.020787   .0213368   329.05   0.000     6.977471    7.064103
----------------+----------------------------------------------------------------
        sigma_u |  5.3462831
        sigma_e |  7.8998009
            rho |  .31413199   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dmfgwages_bls90) nocons /*
> */ ctitle(ATA7_PA_c3) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dmfgwages_bls90 if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,328
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0000                                         min =          1
     between = 0.0323                                         avg =       33.2
     overall = 0.0000                                         max =         88

                                                F(1,39)           =       0.25
corr(u_i, Xb)  = 0.0035                         Prob > F          =     0.6179

                               (Std. Err. adjusted for 40 clusters in state_fips)
---------------------------------------------------------------------------------
                |               Robust
dcap30mile62_38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
dmfgwages_bls90 |  -.0005032   .0010009    -0.50   0.618    -.0025276    .0015212
          _cons |   1.112177   .0003096  3592.04   0.000     1.111551    1.112803
----------------+----------------------------------------------------------------
        sigma_u |  1.3396805
        sigma_e |   2.611584
            rho |    .208325   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dmfgwages_bls90) nocons /*
> */ ctitle(ATA7_PA_c4) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *retail payroll per worker
. xtreg dcap30mile62_38 retwages_bls90 if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.1495                                         min =          1
     between = 0.2003                                         avg =       12.0
     overall = 0.1946                                         max =         38

                                                F(1,35)           =      12.53
corr(u_i, Xb)  = -0.0112                        Prob > F          =     0.0012

                              (Std. Err. adjusted for 36 clusters in state_fips)
--------------------------------------------------------------------------------
               |               Robust
dcap30mile6~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
retwages_bls90 |   2.595401   .7332584     3.54   0.001     1.106808    4.083995
         _cons |  -13.00806   5.606349    -2.32   0.026    -24.38956   -1.626571
---------------+----------------------------------------------------------------
       sigma_u |  5.0093407
       sigma_e |  7.1428369
           rho |  .32968471   (fraction of variance due to u_i)
--------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(retwages_bls90) nocons /*
> */ ctitle(ATA7_PA_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 retwages_bls90 if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,595
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0001                                         min =          2
     between = 0.0320                                         avg =       39.9
     overall = 0.0005                                         max =        124

                                                F(1,39)           =       1.81
corr(u_i, Xb)  = 0.0388                         Prob > F          =     0.1862

                              (Std. Err. adjusted for 40 clusters in state_fips)
--------------------------------------------------------------------------------
               |               Robust
dcap30mile6~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
---------------+----------------------------------------------------------------
retwages_bls90 |   .0032121   .0023871     1.35   0.186    -.0016164    .0080405
         _cons |   1.015931   .0162975    62.34   0.000     .9829659    1.048896
---------------+----------------------------------------------------------------
       sigma_u |  1.2972944
       sigma_e |   2.536889
           rho |  .20729384   (fraction of variance due to u_i)
--------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(retwages_bls90) nocons /*
> */ ctitle(ATA7_PA_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dretwages_bls90 if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0002                                         min =          1
     between = 0.0225                                         avg =       12.0
     overall = 0.0002                                         max =         38

                                                F(1,35)           =       0.15
corr(u_i, Xb)  = 0.0055                         Prob > F          =     0.7025

                               (Std. Err. adjusted for 36 clusters in state_fips)
---------------------------------------------------------------------------------
                |               Robust
dcap30mile62_38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
dretwages_bls90 |  -.1215538   .3156555    -0.39   0.703    -.7623686    .5192609
          _cons |   6.630663   .5328675    12.44   0.000     5.548885    7.712442
----------------+----------------------------------------------------------------
        sigma_u |  5.4097049
        sigma_e |  7.7443554
            rho |  .32793506   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dretwages_bls90) nocons /*
> */ ctitle(ATA7_PA_c3) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dretwages_bls90 if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,594
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0001                                         min =          2
     between = 0.0161                                         avg =       39.9
     overall = 0.0007                                         max =        124

                                                F(1,39)           =       1.25
corr(u_i, Xb)  = 0.0500                         Prob > F          =     0.2705

                               (Std. Err. adjusted for 40 clusters in state_fips)
---------------------------------------------------------------------------------
                |               Robust
dcap30mile62_38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
dretwages_bls90 |   .0028222   .0025247     1.12   0.270    -.0022845    .0079289
          _cons |    1.04368   .0046239   225.71   0.000     1.034327    1.053033
----------------+----------------------------------------------------------------
        sigma_u |   1.297871
        sigma_e |  2.5374064
            rho |  .20737285   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dretwages_bls90) nocons /*
> */ ctitle(ATA7_PA_c4) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *railroad miles, 1911
. xtreg dcap30mile62_38 railroads if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0158                                         min =          1
     between = 0.0120                                         avg =       12.0
     overall = 0.0257                                         max =         38

                                                F(1,35)           =       2.39
corr(u_i, Xb)  = 0.0651                         Prob > F          =     0.1308

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   railroads |   .0150967   .0097571     1.55   0.131    -.0047114    .0349047
       _cons |   5.331501   .9722858     5.48   0.000     3.357656    7.305346
-------------+----------------------------------------------------------------
     sigma_u |  5.3675966
     sigma_e |  7.6835389
         rho |  .32796578   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(railroads) nocons /*
> */ ctitle(ATA7_PA_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 railroads if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0002                                         min =          2
     between = 0.1226                                         avg =       39.9
     overall = 0.0015                                         max =        124

                                                F(1,39)           =       0.12
corr(u_i, Xb)  = 0.0686                         Prob > F          =     0.7329

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   railroads |   .0007225   .0021018     0.34   0.733    -.0035288    .0049738
       _cons |   .9832807   .1637156     6.01   0.000     .6521347    1.314427
-------------+----------------------------------------------------------------
     sigma_u |  1.2826382
     sigma_e |   2.537259
         rho |  .20353737   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(railroads) nocons /*
> */ ctitle(ATA7_PA_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *predicted interstate highway, 1944
. xtreg dcap30mile62_38 inst1944 if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0357                                         min =          1
     between = 0.1220                                         avg =       12.0
     overall = 0.0436                                         max =         38

                                                F(1,35)           =      14.26
corr(u_i, Xb)  = 0.0811                         Prob > F          =     0.0006

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    inst1944 |   3.033146    .803335     3.78   0.001     1.402289    4.664003
       _cons |   5.048347   .4734271    10.66   0.000     4.087238    6.009455
-------------+----------------------------------------------------------------
     sigma_u |  5.1971915
     sigma_e |  7.6054136
         rho |   .3183242   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(inst1944) nocons /*
> */ ctitle(ATA7_PA_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 inst1944 if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0012                                         min =          2
     between = 0.0725                                         avg =       39.9
     overall = 0.0052                                         max =        124

                                                F(1,39)           =       0.93
corr(u_i, Xb)  = 0.1151                         Prob > F          =     0.3411

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    inst1944 |   .1946592   .2019694     0.96   0.341    -.2138624    .6031808
       _cons |   .9791859   .0626409    15.63   0.000     .8524828    1.105889
-------------+----------------------------------------------------------------
     sigma_u |  1.2875846
     sigma_e |  2.5359838
         rho |  .20495191   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(inst1944) nocons /*
> */ ctitle(ATA7_PA_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. 
. ****************************************
. ***PANEL B
. ****************************************
. *infant mortality rate
. xtreg dcap30mile62_38 imr if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0066                                         min =          1
     between = 0.0159                                         avg =       12.0
     overall = 0.0287                                         max =         38

                                                F(1,35)           =       2.31
corr(u_i, Xb)  = 0.1595                         Prob > F          =     0.1377

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         imr |  -.0461176   .0303564    -1.52   0.138    -.1077443    .0155091
       _cons |    8.74532   1.256878     6.96   0.000     6.193722    11.29692
-------------+----------------------------------------------------------------
     sigma_u |    5.35942
     sigma_e |  7.7194044
         rho |  .32524676   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(imr) nocons /*
> */ ctitle(ATA7_PB_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 imr if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0000                                         min =          2
     between = 0.1477                                         avg =       39.9
     overall = 0.0036                                         max =        124

                                                F(1,39)           =       0.00
corr(u_i, Xb)  = -0.1804                        Prob > F          =     0.9618

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
         imr |  -.0002561   .0053067    -0.05   0.962    -.0109899    .0104778
       _cons |   1.050157   .2196201     4.78   0.000     .6059338    1.494381
-------------+----------------------------------------------------------------
     sigma_u |  1.2982699
     sigma_e |  2.5374974
         rho |  .20746211   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(imr) nocons /*
> */ ctitle(ATA7_PB_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dimr if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        429
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0024                                         min =          1
     between = 0.0043                                         avg =       11.9
     overall = 0.0073                                         max =         38

                                                F(1,35)           =       0.92
corr(u_i, Xb)  = 0.0742                         Prob > F          =     0.3432

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        dimr |   -.022274   .0231786    -0.96   0.343    -.0693292    .0247811
       _cons |   6.514047   .3219219    20.23   0.000     5.860511    7.167583
-------------+----------------------------------------------------------------
     sigma_u |  5.3868023
     sigma_e |  7.7538055
         rho |  .32553197   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dimr) nocons /*
> */ ctitle(ATA7_PB_c3) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dimr if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,594
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0017                                         min =          2
     between = 0.0074                                         avg =       39.9
     overall = 0.0006                                         max =        124

                                                F(1,39)           =       3.46
corr(u_i, Xb)  = -0.0434                        Prob > F          =     0.0703

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        dimr |  -.0051524   .0027684    -1.86   0.070     -.010752    .0004473
       _cons |   .9730906   .0341067    28.53   0.000     .9041033    1.042078
-------------+----------------------------------------------------------------
     sigma_u |  1.2940469
     sigma_e |   2.536177
         rho |  .20656333   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dimr) nocons /*
> */ ctitle(ATA7_PB_c4) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *percent urban
. xtreg dcap30mile62_38 ppopurb if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0671                                         min =          1
     between = 0.1328                                         avg =       12.0
     overall = 0.1021                                         max =         38

                                                F(1,35)           =       9.56
corr(u_i, Xb)  = 0.1433                         Prob > F          =     0.0039

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     ppopurb |   .0757473      .0245     3.09   0.004     .0260097    .1254849
       _cons |    3.90548   .9478135     4.12   0.000     1.981316    5.829643
-------------+----------------------------------------------------------------
     sigma_u |  5.0313655
     sigma_e |  7.4806981
         rho |   .3114671   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ppopurb) nocons /*
> */ ctitle(ATA7_PB_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 ppopurb if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0037                                         min =          2
     between = 0.1336                                         avg =       39.9
     overall = 0.0088                                         max =        124

                                                F(1,39)           =       6.28
corr(u_i, Xb)  = 0.0960                         Prob > F          =     0.0165

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     ppopurb |   .0076597    .003057     2.51   0.017     .0014763    .0138432
       _cons |   .8806121   .0634368    13.88   0.000     .7522991    1.008925
-------------+----------------------------------------------------------------
     sigma_u |  1.2701566
     sigma_e |  2.5327731
         rho |  .20095293   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(ppopurb) nocons /*
> */ ctitle(ATA7_PB_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dppopurb if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0025                                         min =          1
     between = 0.0280                                         avg =       12.0
     overall = 0.0000                                         max =         38

                                                F(1,35)           =       1.40
corr(u_i, Xb)  = -0.0824                        Prob > F          =     0.2441

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    dppopurb |   .0643276      .0543     1.18   0.244    -.0459073    .1745624
       _cons |   6.808177   .0233694   291.33   0.000     6.760735    6.855619
-------------+----------------------------------------------------------------
     sigma_u |  5.4271462
     sigma_e |  7.7354686
         rho |  .32986289   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dppopurb) nocons /*
> */ ctitle(ATA7_PB_c3) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dppopurb if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0015                                         min =          2
     between = 0.0252                                         avg =       39.9
     overall = 0.0047                                         max =        124

                                                F(1,39)           =       4.40
corr(u_i, Xb)  = 0.0893                         Prob > F          =     0.0424

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
    dppopurb |  -.0173698   .0082779    -2.10   0.042    -.0341135   -.0006262
       _cons |   1.076447   .0175795    61.23   0.000     1.040889    1.112005
-------------+----------------------------------------------------------------
     sigma_u |  1.2861714
     sigma_e |   2.535578
         rho |  .20464635   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dppopurb) nocons /*
> */ ctitle(ATA7_PB_c4) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *percent white
. xtreg dcap30mile62_38 pwhite if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0046                                         min =          1
     between = 0.0006                                         avg =       12.0
     overall = 0.0033                                         max =         38

                                                F(1,35)           =       1.13
corr(u_i, Xb)  = -0.2348                        Prob > F          =     0.2953

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      pwhite |  -.0687489   .0647072    -1.06   0.295    -.2001116    .0626137
       _cons |   13.17098   5.962679     2.21   0.034       1.0661    25.27586
-------------+----------------------------------------------------------------
     sigma_u |  5.4671184
     sigma_e |  7.7273193
         rho |  .33358372   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(pwhite) nocons /*
> */ ctitle(ATA7_PB_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 pwhite if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0002                                         min =          2
     between = 0.0002                                         avg =       39.9
     overall = 0.0000                                         max =        124

                                                F(1,39)           =       0.40
corr(u_i, Xb)  = -0.0262                        Prob > F          =     0.5300

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      pwhite |  -.0018843   .0029735    -0.63   0.530    -.0078988    .0041303
       _cons |   1.207544   .2650955     4.56   0.000     .6713376     1.74375
-------------+----------------------------------------------------------------
     sigma_u |  1.2974314
     sigma_e |  2.5372952
         rho |  .20727593   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(pwhite) nocons /*
> */ ctitle(ATA7_PB_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dpwhite if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        431
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0008                                         min =          1
     between = 0.0069                                         avg =       12.0
     overall = 0.0002                                         max =         38

                                                F(1,35)           =       1.48
corr(u_i, Xb)  = -0.0626                        Prob > F          =     0.2321

                            (Std. Err. adjusted for 36 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     dpwhite |   .0659946   .0542685     1.22   0.232    -.0441762    .1761655
       _cons |   6.813948   .0180206   378.12   0.000     6.777364    6.850531
-------------+----------------------------------------------------------------
     sigma_u |  5.4071685
     sigma_e |  7.7421245
         rho |  .32785534   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dpwhite) nocons /*
> */ ctitle(ATA7_PB_c3) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dpwhite if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,596
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0001                                         min =          2
     between = 0.0442                                         avg =       39.9
     overall = 0.0001                                         max =        124

                                                F(1,39)           =       0.27
corr(u_i, Xb)  = 0.0118                         Prob > F          =     0.6045

                            (Std. Err. adjusted for 40 clusters in state_fips)
------------------------------------------------------------------------------
             |               Robust
dcap30mil~38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
     dpwhite |   .0015539   .0029756     0.52   0.604    -.0044647    .0075725
       _cons |   1.037721   .0035213   294.70   0.000     1.030598    1.044843
-------------+----------------------------------------------------------------
     sigma_u |  1.2956552
     sigma_e |  2.5374161
         rho |  .20681045   (fraction of variance due to u_i)
------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dpwhite) nocons /*
> */ ctitle(ATA7_PB_c4) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. *log(median dwelling rent)
. xtreg dcap30mile62_38 lnmrhouse_bls90 if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        430
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.1587                                         min =          1
     between = 0.2160                                         avg =       11.9
     overall = 0.1965                                         max =         38

                                                F(1,35)           =      17.22
corr(u_i, Xb)  = -0.1175                        Prob > F          =     0.0002

                               (Std. Err. adjusted for 36 clusters in state_fips)
---------------------------------------------------------------------------------
                |               Robust
dcap30mile62_38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
lnmrhouse_bls90 |   8.144093   1.962701     4.15   0.000     4.159598    12.12859
          _cons |  -31.91943   9.343737    -3.42   0.002    -50.88823   -12.95064
----------------+----------------------------------------------------------------
        sigma_u |  5.1143385
        sigma_e |  7.1130688
            rho |  .34079096   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(lnmrhouse_bls90) nocons /*
> */ ctitle(ATA7_PB_c1) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 lnmrhouse_bls90 if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,594
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0028                                         min =          2
     between = 0.0020                                         avg =       39.9
     overall = 0.0014                                         max =        124

                                                F(1,39)           =       1.25
corr(u_i, Xb)  = -0.1174                        Prob > F          =     0.2707

                               (Std. Err. adjusted for 40 clusters in state_fips)
---------------------------------------------------------------------------------
                |               Robust
dcap30mile62_38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
lnmrhouse_bls90 |   .4131767   .3697643     1.12   0.271    -.3347422    1.161096
          _cons |  -.7880127    1.63675    -0.48   0.633    -4.098653    2.522628
----------------+----------------------------------------------------------------
        sigma_u |  1.3013403
        sigma_e |  2.5355559
            rho |  .20849249   (fraction of variance due to u_i)
---------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(lnmrhouse_bls90) nocons /*
> */ ctitle(ATA7_PB_c2) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dlnmrhouse_bls90 if year==1940 & bcap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =        429
Group variable: state_fips                      Number of groups  =         36

R-sq:                                           Obs per group:
     within  = 0.0002                                         min =          1
     between = 0.0719                                         avg =       11.9
     overall = 0.0116                                         max =         38

                                                F(1,35)           =       0.05
corr(u_i, Xb)  = 0.1570                         Prob > F          =     0.8330

                                (Std. Err. adjusted for 36 clusters in state_fips)
----------------------------------------------------------------------------------
                 |               Robust
 dcap30mile62_38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
dlnmrhouse_bls90 |   .7268888   3.422558     0.21   0.833    -6.221273    7.675051
           _cons |   6.916391   .2291158    30.19   0.000     6.451261    7.381521
-----------------+----------------------------------------------------------------
         sigma_u |  5.3666553
         sigma_e |  7.7603792
             rho |  .32351765   (fraction of variance due to u_i)
----------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dlnmrhouse_bls90) nocons /*
> */ ctitle(ATA7_PB_c3) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. xtreg dcap30mile62_38 dlnmrhouse_bls90 if year==1940 & scap1940==1, fe cluster(state_fips)

Fixed-effects (within) regression               Number of obs     =      1,581
Group variable: state_fips                      Number of groups  =         40

R-sq:                                           Obs per group:
     within  = 0.0015                                         min =          2
     between = 0.0474                                         avg =       39.5
     overall = 0.0116                                         max =        123

                                                F(1,39)           =       1.31
corr(u_i, Xb)  = 0.1933                         Prob > F          =     0.2586

                                (Std. Err. adjusted for 40 clusters in state_fips)
----------------------------------------------------------------------------------
                 |               Robust
 dcap30mile62_38 |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-----------------+----------------------------------------------------------------
dlnmrhouse_bls90 |   .5471612   .4772486     1.15   0.259    -.4181652    1.512488
           _cons |   1.129962   .0800775    14.11   0.000     .9679905    1.291934
-----------------+----------------------------------------------------------------
         sigma_u |  1.2736789
         sigma_e |   2.525231
             rho |  .20280634   (fraction of variance due to u_i)
----------------------------------------------------------------------------------

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(dlnmrhouse_bls90) nocons /*
> */ ctitle(ATA7_PB_c4) se bdec(4) sdec(4) rdec(3) addstat("R2W",`e(r2_w)') excel append
logfiles/Canary_output.xml
dir : seeout

. 
. 
. ********************************************************************************
. ********************************************************************************
. ***APPENDIX TABLE A.8
. ********************************************************************************
. ********************************************************************************
. clear all

. use data/imr_final_balanced.dta, clear
(U.S. County-Level Natality and Mortality Data, 1915-2007)

. 
. global Geo c.year#c.laty c.year#c.lony yprcp ytav ydda29 yddb10

. global Geo3 c.year#c.lat c.year#c.lon yprcpm ytavm ydda29m yddb10m

. 
. global Econ c.year#c.lnpop1940 c.year#c.lnemp1940 c.year#c.lnmfg1940 c.year#c.railroads c.year#c.inst1944

. global Econ3nln c.year#c.pop1940 c.year#c.emp1940 c.year#c.mfg1940 c.year#c.railroads c.year#c.inst1944

. 
. ****************************************
. ***PANEL A
. ****************************************
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mile /*
> */ if dist30_1960<=90 [fw=births_rs], /*
> */ absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  13,   2026) =      15.36
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6791
                                                  Adj R-squared   =     0.6791
                                                  Within R-sq.    =     0.0248
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8842

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0620637   .0121531     5.11   0.000     .0382297    .0858976
                   |
     c.year#c.lony |   .0337393   .0080195     4.21   0.000      .018012    .0494666
                   |
             yprcp |   .0001799   .0002722     0.66   0.509     -.000354    .0007138
              ytav |   .2591277   .1579341     1.64   0.101    -.0506025     .568858
            ydda29 |  -.0057437   .0031951    -1.80   0.072    -.0120097    .0005222
            yddb10 |   .0000995   .0006777     0.15   0.883    -.0012296    .0014286
                   |
c.year#c.lnpop1940 |  -.2131122   .1168471    -1.82   0.068    -.4422652    .0160408
                   |
c.year#c.lnemp1940 |   .3551562   .1155706     3.07   0.002     .1285066    .5818059
                   |
c.year#c.lnmfg1940 |  -.1135736   .0179896    -6.31   0.000    -.1488537   -.0782935
                   |
c.year#c.railroads |  -.0001563   .0001758    -0.89   0.374    -.0005011    .0001884
                   |
 c.year#c.inst1944 |  -.0318023   .0253768    -1.25   0.210    -.0815697     .017965
                   |
   cap30mile_hydro |   .0492161     .06418     0.77   0.443    -.0766495    .1750817
         cap30mile |   .1874939   .0268736     6.98   0.000     .1347912    .2401966
             _cons |   592.4891    1584.16     0.37   0.708    -2514.263    3699.242
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mile) nocons /*
> */ ctitle(ATA8_PA_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mile /*
> */ if (cap30mile_1962>0 & cap30mile_1962~=.) [fw=births_rs], /*
> */ absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 47,381,833
Absorbing 2 HDFE groups                           F(  13,    919) =      16.28
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7447
                                                  Adj R-squared   =     0.7447
                                                  Within R-sq.    =     0.0444
Number of clusters (county_fips) =        920     Root MSE        =     4.7586

                                (Std. Err. adjusted for 920 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0798334   .0149916     5.33   0.000     .0504116    .1092551
                   |
     c.year#c.lony |   .0424988   .0088717     4.79   0.000     .0250877    .0599099
                   |
             yprcp |   .0002372    .000382     0.62   0.535    -.0005125    .0009869
              ytav |   .3084267    .177826     1.73   0.083    -.0405655    .6574188
            ydda29 |  -.0053288   .0030475    -1.75   0.081    -.0113097    .0006522
            yddb10 |  -.0004209   .0008147    -0.52   0.606    -.0020199     .001178
                   |
c.year#c.lnpop1940 |  -.2350182   .1505252    -1.56   0.119    -.5304313    .0603949
                   |
c.year#c.lnemp1940 |   .4062651    .151159     2.69   0.007     .1096082    .7029221
                   |
c.year#c.lnmfg1940 |  -.1278681   .0248016    -5.16   0.000    -.1765425   -.0791938
                   |
c.year#c.railroads |  -.0001325   .0001593    -0.83   0.406    -.0004451      .00018
                   |
 c.year#c.inst1944 |  -.0563939   .0320278    -1.76   0.079      -.11925    .0064622
                   |
   cap30mile_hydro |   .0885695   .0497336     1.78   0.075    -.0090351    .1861742
         cap30mile |   .1535658   .0274328     5.60   0.000     .0997276    .2074041
             _cons |   335.9949   1834.157     0.18   0.855    -3263.627    3935.617
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |       920         920           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mile) nocons /*
> */ ctitle(ATA8_PA_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap50mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  13,   2026) =      11.81
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6784
                                                  Adj R-squared   =     0.6784
                                                  Within R-sq.    =     0.0227
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8906

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0635053   .0123523     5.14   0.000     .0392807    .0877299
                   |
     c.year#c.lony |    .036448    .008141     4.48   0.000     .0204823    .0524137
                   |
             yprcp |   .0001895   .0002729     0.69   0.488    -.0003457    .0007246
              ytav |   .2597181   .1594815     1.63   0.104    -.0530468     .572483
            ydda29 |  -.0060128   .0031769    -1.89   0.059    -.0122431    .0002174
            yddb10 |   .0001531   .0006833     0.22   0.823     -.001187    .0014933
                   |
c.year#c.lnpop1940 |  -.2031287   .1189892    -1.71   0.088    -.4364826    .0302253
                   |
c.year#c.lnemp1940 |   .3681254   .1172264     3.14   0.002     .1382285    .5980223
                   |
c.year#c.lnmfg1940 |  -.1217226   .0182964    -6.65   0.000    -.1576043   -.0858408
                   |
c.year#c.railroads |  -.0001643   .0001903    -0.86   0.388    -.0005374    .0002089
                   |
 c.year#c.inst1944 |  -.0354001   .0256403    -1.38   0.168    -.0856843    .0148841
                   |
   cap30mile_hydro |    .052428   .0633707     0.83   0.408    -.0718506    .1767065
         cap50mile |   .1050101   .0174882     6.00   0.000     .0707134    .1393067
             _cons |   589.1333   1583.649     0.37   0.710    -2516.617    3694.884
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap50mile) nocons /*
> */ ctitle(ATA8_PA_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap100mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  13,   2026) =      10.63
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6780
                                                  Adj R-squared   =     0.6780
                                                  Within R-sq.    =     0.0213
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8949

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0645366   .0124292     5.19   0.000     .0401613     .088912
                   |
     c.year#c.lony |   .0321848   .0084465     3.81   0.000       .01562    .0487496
                   |
             yprcp |    .000172   .0002743     0.63   0.531    -.0003659      .00071
              ytav |   .2520254    .159254     1.58   0.114    -.0602932    .5643441
            ydda29 |  -.0054471   .0033835    -1.61   0.108    -.0120826    .0011884
            yddb10 |  -4.58e-06   .0006821    -0.01   0.995    -.0013423    .0013332
                   |
c.year#c.lnpop1940 |  -.2030146   .1199589    -1.69   0.091    -.4382703    .0322411
                   |
c.year#c.lnemp1940 |   .3791193   .1183298     3.20   0.001     .1470586      .61118
                   |
c.year#c.lnmfg1940 |  -.1253707    .018483    -6.78   0.000    -.1616183   -.0891231
                   |
c.year#c.railroads |  -.0000895   .0001972    -0.45   0.650    -.0004762    .0002972
                   |
 c.year#c.inst1944 |  -.0368065   .0261833    -1.41   0.160    -.0881555    .0145426
                   |
   cap30mile_hydro |   .0668638    .058315     1.15   0.252    -.0474998    .1812275
        cap100mile |   .0646407   .0111375     5.80   0.000     .0427985    .0864829
             _cons |  -401.6988   1632.203    -0.25   0.806    -3602.671    2799.273
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap100mile) nocons /*
> */ ctitle(ATA8_PA_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnimr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,468,665
Absorbing 2 HDFE groups                           F(  13,   2026) =      12.93
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6403
                                                  Adj R-squared   =     0.6403
                                                  Within R-sq.    =     0.0229
Number of clusters (county_fips) =      2,027     Root MSE        =     0.1926

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0016317   .0003349     4.87   0.000      .000975    .0022884
                   |
     c.year#c.lony |   .0009894   .0002097     4.72   0.000     .0005781    .0014006
                   |
             yprcp |   6.87e-06   8.13e-06     0.84   0.399    -9.08e-06    .0000228
              ytav |   .0064553   .0043476     1.48   0.138    -.0020709    .0149815
            ydda29 |  -.0001143   .0000941    -1.21   0.225    -.0002989    .0000703
            yddb10 |  -2.73e-06   .0000199    -0.14   0.891    -.0000418    .0000364
                   |
c.year#c.lnpop1940 |  -.0047717   .0031102    -1.53   0.125    -.0108713    .0013279
                   |
c.year#c.lnemp1940 |   .0098032   .0030963     3.17   0.002      .003731    .0158754
                   |
c.year#c.lnmfg1940 |  -.0034188   .0005083    -6.73   0.000    -.0044157   -.0024219
                   |
c.year#c.railroads |  -5.83e-06   4.86e-06    -1.20   0.231    -.0000154    3.70e-06
                   |
 c.year#c.inst1944 |  -.0012245   .0006762    -1.81   0.070    -.0025506    .0001016
                   |
   cap30mile_hydro |   .0015942   .0017864     0.89   0.372    -.0019092    .0050976
         cap30mile |   .0053036   .0008212     6.46   0.000     .0036931     .006914
             _cons |   15.16328   41.22538     0.37   0.713    -65.68528    96.01184
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mile) nocons /*
> */ ctitle(ATA8_PA_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ /*
> */ cap30mile_hydro /*
> */ if n0==25 [fw=births_rs], /*
> */ absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 15,268,355
Absorbing 2 HDFE groups                           F(  12,   1080) =       5.50
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5908
                                                  Adj R-squared   =     0.5907
                                                  Within R-sq.    =     0.0119
Number of clusters (county_fips) =      1,081     Root MSE        =     8.1480

                              (Std. Err. adjusted for 1,081 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0198416   .0158816     1.25   0.212    -.0113208     .051004
                   |
     c.year#c.lony |   .0013282    .012401     0.11   0.915    -.0230047    .0256611
                   |
             yprcp |  -.0000973   .0003294    -0.30   0.768    -.0007436     .000549
              ytav |   -.261749   .2377494    -1.10   0.271    -.7282522    .2047542
            ydda29 |    .003519   .0092326     0.38   0.703    -.0145967    .0216348
            yddb10 |  -.0005393    .000944    -0.57   0.568    -.0023915    .0013129
                   |
c.year#c.lnpop1940 |  -.2997618   .1677037    -1.79   0.074    -.6288237    .0293001
                   |
c.year#c.lnemp1940 |   .2112883   .1604927     1.32   0.188    -.1036246    .5262012
                   |
c.year#c.lnmfg1940 |  -.0687019   .0234627    -2.93   0.003    -.1147394   -.0226643
                   |
c.year#c.railroads |   .0002227   .0002539     0.88   0.380    -.0002754    .0007208
                   |
 c.year#c.inst1944 |   .0973308   .0340212     2.86   0.004     .0305756     .164086
                   |
   cap30mile_hydro |  -.9050211   .4943073    -1.83   0.067    -1.874933    .0648904
             _cons |   1904.417   2349.066     0.81   0.418    -2704.833    6513.668
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      1081        1081           0    *|
   state_fips#year |      1000           0        1000     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mile_hydro) nocons /*
> */ ctitle(ATA8_PA_c6) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. *n0:number of obs before coal plant openings
. *if n0=25, then there's no coal plant in the county
. 
. reghdfe imr /*
> */ $Geo $Econ /*
> */ cap50mile_hydro /*
> */ if n0==25 [fw=births_rs], /*
> */ absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 15,268,355
Absorbing 2 HDFE groups                           F(  12,   1080) =       5.67
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.5909
                                                  Adj R-squared   =     0.5908
                                                  Within R-sq.    =     0.0122
Number of clusters (county_fips) =      1,081     Root MSE        =     8.1470

                              (Std. Err. adjusted for 1,081 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0212665   .0159265     1.34   0.182    -.0099838    .0525169
                   |
     c.year#c.lony |   .0012299   .0124535     0.10   0.921    -.0232058    .0256657
                   |
             yprcp |  -.0000848   .0003278    -0.26   0.796     -.000728    .0005585
              ytav |   -.266862   .2373406    -1.12   0.261    -.7325629    .1988389
            ydda29 |   .0038464   .0091203     0.42   0.673    -.0140491    .0217418
            yddb10 |  -.0005783   .0009452    -0.61   0.541    -.0024329    .0012762
                   |
c.year#c.lnpop1940 |  -.2936199    .166882    -1.76   0.079    -.6210696    .0338298
                   |
c.year#c.lnemp1940 |   .2058249   .1598269     1.29   0.198    -.1077815    .5194312
                   |
c.year#c.lnmfg1940 |  -.0692986   .0234023    -2.96   0.003    -.1152178   -.0233794
                   |
c.year#c.railroads |   .0002433   .0002534     0.96   0.337     -.000254    .0007407
                   |
 c.year#c.inst1944 |   .0950691   .0339874     2.80   0.005     .0283802     .161758
                   |
   cap50mile_hydro |  -.5054999     .19854    -2.55   0.011    -.8950678   -.1159321
             _cons |    1762.04   2350.103     0.75   0.454    -2849.244    6373.325
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      1081        1081           0    *|
   state_fips#year |      1000           0        1000     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap50mile_hydro) nocons /*
> */ ctitle(ATA8_PA_c7) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL B
. ****************************************
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile  /*
> */ if dist30_1960<=90 [fw=births_rs], /*
> */ absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      15.91
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6795
                                                  Adj R-squared   =     0.6795
                                                  Within R-sq.    =     0.0259
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8808

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0604739   .0121726     4.97   0.000     .0366018    .0843459
                   |
     c.year#c.lony |      .0303   .0080368     3.77   0.000     .0145388    .0460611
                   |
             yprcp |   .0001958   .0002724     0.72   0.472    -.0003384      .00073
              ytav |   .2606794   .1586635     1.64   0.101    -.0504813      .57184
            ydda29 |  -.0056702   .0031928    -1.78   0.076    -.0119317    .0005912
            yddb10 |   .0001614   .0006793     0.24   0.812    -.0011708    .0014936
                   |
c.year#c.lnpop1940 |   -.209495   .1151003    -1.82   0.069    -.4352224    .0162324
                   |
c.year#c.lnemp1940 |   .3430162   .1137293     3.02   0.003     .1199777    .5660548
                   |
c.year#c.lnmfg1940 |  -.1100548   .0179688    -6.12   0.000     -.145294   -.0748156
                   |
c.year#c.railroads |  -.0001606   .0001735    -0.93   0.355    -.0005008    .0001796
                   |
 c.year#c.inst1944 |  -.0300809   .0251455    -1.20   0.232    -.0793945    .0192328
                   |
   cap30mile_hydro |   .1166962   .0634755     1.84   0.066    -.0077877    .2411802
 scap1940cap30mile |  -.0401813   .0575558    -0.70   0.485    -.1530561    .0726935
 bcap1940cap30mile |   .2030099    .027574     7.36   0.000     .1489335    .2570862
             _cons |   239.9315   1582.933     0.15   0.880    -2864.416    3344.279
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons  /*
> */ ctitle(ATA8_PB_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile  /*
> */ if (cap30mile_1962>0 & cap30mile_1962~=.) [fw=births_rs], /*
> */ absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 47,381,833
Absorbing 2 HDFE groups                           F(  14,    919) =      15.96
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7451
                                                  Adj R-squared   =     0.7451
                                                  Within R-sq.    =     0.0460
Number of clusters (county_fips) =        920     Root MSE        =     4.7546

                                (Std. Err. adjusted for 920 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0786782   .0152025     5.18   0.000     .0488426    .1085137
                   |
     c.year#c.lony |   .0393813   .0089428     4.40   0.000     .0218306     .056932
                   |
             yprcp |   .0002552   .0003811     0.67   0.503    -.0004927    .0010032
              ytav |    .313621   .1787343     1.75   0.080    -.0371538    .6643959
            ydda29 |  -.0051749   .0030141    -1.72   0.086    -.0110901    .0007404
            yddb10 |  -.0003283   .0008186    -0.40   0.688    -.0019348    .0012782
                   |
c.year#c.lnpop1940 |  -.2250225   .1480466    -1.52   0.129    -.5155712    .0655262
                   |
c.year#c.lnemp1940 |   .3881405   .1487073     2.61   0.009     .0962951    .6799858
                   |
c.year#c.lnmfg1940 |  -.1260331   .0247242    -5.10   0.000    -.1745556   -.0775106
                   |
c.year#c.railroads |  -.0001344    .000157    -0.86   0.392    -.0004426    .0001737
                   |
 c.year#c.inst1944 |  -.0561034   .0315317    -1.78   0.076    -.1179859    .0057791
                   |
   cap30mile_hydro |   .1501711   .0508783     2.95   0.003       .05032    .2500223
 scap1940cap30mile |  -.0534264   .0593983    -0.90   0.369    -.1699986    .0631457
 bcap1940cap30mile |   .1649326   .0278774     5.92   0.000     .1102218    .2196433
             _cons |   25.15593   1841.182     0.01   0.989    -3588.253    3638.564
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |       920         920           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons  /*
> */ ctitle(ATA8_PB_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ scap1940cap50mile bcap1940cap50mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      12.59
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6789
                                                  Adj R-squared   =     0.6789
                                                  Within R-sq.    =     0.0241
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8864

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0617938   .0124562     4.96   0.000     .0373656     .086222
                   |
     c.year#c.lony |   .0343956   .0081492     4.22   0.000      .018414    .0503772
                   |
             yprcp |   .0002081   .0002732     0.76   0.446    -.0003277    .0007439
              ytav |   .2621418   .1606346     1.63   0.103    -.0528843    .5771679
            ydda29 |  -.0058997   .0031557    -1.87   0.062    -.0120885    .0002891
            yddb10 |   .0002362   .0006871     0.34   0.731    -.0011112    .0015837
                   |
c.year#c.lnpop1940 |  -.2098379   .1180413    -1.78   0.076    -.4413329    .0216572
                   |
c.year#c.lnemp1940 |   .3630164   .1161294     3.13   0.002     .1352708     .590762
                   |
c.year#c.lnmfg1940 |  -.1189317   .0182661    -6.51   0.000     -.154754   -.0831094
                   |
c.year#c.railroads |  -.0001678   .0001876    -0.89   0.371    -.0005358    .0002002
                   |
 c.year#c.inst1944 |  -.0349744   .0252632    -1.38   0.166     -.084519    .0145702
                   |
   cap30mile_hydro |   .1003356   .0652576     1.54   0.124    -.0276434    .2283146
 scap1940cap50mile |   .0002585   .0276509     0.01   0.993    -.0539687    .0544858
 bcap1940cap50mile |   .1187123   .0179763     6.60   0.000     .0834583    .1539664
             _cons |   585.5688   1577.779     0.37   0.711    -2508.669    3679.807
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap50mile bcap1940cap50mile) nocons  /*
> */ ctitle(ATA8_PB_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ scap1940cap100mile bcap1940cap100mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      12.19
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6785
                                                  Adj R-squared   =     0.6785
                                                  Within R-sq.    =     0.0229
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8898

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0626869   .0125093     5.01   0.000     .0381544    .0872194
                   |
     c.year#c.lony |   .0296467   .0084419     3.51   0.000     .0130911    .0462024
                   |
             yprcp |    .000184   .0002743     0.67   0.502    -.0003539    .0007219
              ytav |   .2568432   .1600647     1.60   0.109    -.0570654    .5707518
            ydda29 |  -.0050948   .0033654    -1.51   0.130    -.0116949    .0015053
            yddb10 |   .0001152   .0006864     0.17   0.867    -.0012309    .0014613
                   |
c.year#c.lnpop1940 |  -.2155344   .1202875    -1.79   0.073    -.4514345    .0203656
                   |
c.year#c.lnemp1940 |    .376738   .1185169     3.18   0.002     .1443104    .6091657
                   |
c.year#c.lnmfg1940 |  -.1232299   .0183917    -6.70   0.000    -.1592984   -.0871613
                   |
c.year#c.railroads |   -.000076   .0001942    -0.39   0.696    -.0004567    .0003048
                   |
 c.year#c.inst1944 |  -.0413371   .0258503    -1.60   0.110    -.0920331    .0093588
                   |
   cap30mile_hydro |   .0897599   .0604574     1.48   0.138    -.0288052     .208325
scap1940cap100mile |   .0150095   .0145799     1.03   0.303    -.0135836    .0436026
bcap1940cap100mile |   .0709483   .0112956     6.28   0.000     .0487962    .0931004
             _cons |  -387.1656   1635.283    -0.24   0.813    -3594.178    2819.847
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap100mile bcap1940cap100mile) nocons  /*
> */ ctitle(ATA8_PB_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnimr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ scap1940cap30mile bcap1940cap30mile /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,468,665
Absorbing 2 HDFE groups                           F(  14,   2026) =      13.20
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6406
                                                  Adj R-squared   =     0.6406
                                                  Within R-sq.    =     0.0237
Number of clusters (county_fips) =      2,027     Root MSE        =     0.1925

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0015883   .0003365     4.72   0.000     .0009284    .0022481
                   |
     c.year#c.lony |   .0008952   .0002115     4.23   0.000     .0004804    .0013101
                   |
             yprcp |   7.30e-06   8.15e-06     0.90   0.370    -8.67e-06    .0000233
              ytav |   .0064997   .0043638     1.49   0.137    -.0020583    .0150577
            ydda29 |  -.0001123   .0000938    -1.20   0.231    -.0002962    .0000716
            yddb10 |  -1.03e-06     .00002    -0.05   0.959    -.0000402    .0000381
                   |
c.year#c.lnpop1940 |  -.0046729   .0030674    -1.52   0.128    -.0106885    .0013427
                   |
c.year#c.lnemp1940 |   .0094723   .0030494     3.11   0.002     .0034921    .0154525
                   |
c.year#c.lnmfg1940 |  -.0033234    .000508    -6.54   0.000    -.0043197   -.0023271
                   |
c.year#c.railroads |  -5.94e-06   4.79e-06    -1.24   0.215    -.0000153    3.46e-06
                   |
 c.year#c.inst1944 |  -.0011776   .0006726    -1.75   0.080    -.0024966    .0001415
                   |
   cap30mile_hydro |   .0034383   .0017459     1.97   0.049     .0000144    .0068623
 scap1940cap30mile |  -.0009183   .0016545    -0.55   0.579     -.004163    .0023265
 bcap1940cap30mile |   .0057275   .0008492     6.74   0.000     .0040622    .0073929
             _cons |   5.498597   41.40127     0.13   0.894    -75.69491    86.69211
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(scap1940cap30mile bcap1940cap30mile) nocons  /*
> */ ctitle(ATA8_PB_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. ****************************************
. ***PANEL C
. ****************************************
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if dist30_1960<=90 [fw=births_rs], /*
> */ absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      14.97
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6794
                                                  Adj R-squared   =     0.6793
                                                  Within R-sq.    =     0.0254
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8823

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0549471   .0123546     4.45   0.000      .030718    .0791762
                   |
     c.year#c.lony |   .0344987   .0079727     4.33   0.000     .0188632    .0501342
                   |
             yprcp |    .000162   .0002726     0.59   0.552    -.0003727    .0006967
              ytav |   .2379916   .1576689     1.51   0.131    -.0712184    .5472017
            ydda29 |  -.0050501   .0030899    -1.63   0.102    -.0111097    .0010095
            yddb10 |   .0000603   .0006829     0.09   0.930     -.001279    .0013995
                   |
c.year#c.lnpop1940 |  -.2278037   .1168584    -1.95   0.051    -.4569788    .0013714
                   |
c.year#c.lnemp1940 |   .3623914   .1151092     3.15   0.002     .1366467    .5881361
                   |
c.year#c.lnmfg1940 |  -.1110418   .0181987    -6.10   0.000    -.1467318   -.0753517
                   |
c.year#c.railroads |  -.0001023   .0001748    -0.59   0.558     -.000445    .0002404
                   |
 c.year#c.inst1944 |  -.0291038   .0252916    -1.15   0.250     -.078704    .0204965
                   |
   cap30mile_hydro |   .0582221   .0655018     0.89   0.374    -.0702358    .1866799
 cap30mileL2wlight |   .0013991   .0429151     0.03   0.974    -.0827632    .0855613
 cap30mileH2wlight |   .1954993    .029639     6.60   0.000     .1373731    .2536254
             _cons |   1381.551   1592.701     0.87   0.386    -1741.951    4505.053
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(ATA8_PC_c1) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ if (cap30mile_1962>0 & cap30mile_1962~=.) [fw=births_rs], /*
> */ absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 47,381,833
Absorbing 2 HDFE groups                           F(  14,    919) =      15.71
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.7448
                                                  Adj R-squared   =     0.7448
                                                  Within R-sq.    =     0.0447
Number of clusters (county_fips) =        920     Root MSE        =     4.7579

                                (Std. Err. adjusted for 920 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0726929   .0153518     4.74   0.000     .0425641    .1028216
                   |
     c.year#c.lony |   .0443971   .0088346     5.03   0.000     .0270587    .0617355
                   |
             yprcp |   .0002054   .0003829     0.54   0.592    -.0005461    .0009569
              ytav |    .291251   .1781958     1.63   0.103    -.0584669    .6409689
            ydda29 |  -.0045938   .0028512    -1.61   0.107    -.0101893    .0010018
            yddb10 |  -.0004453   .0008214    -0.54   0.588    -.0020574    .0011668
                   |
c.year#c.lnpop1940 |  -.2383373    .149868    -1.59   0.112    -.5324605    .0557859
                   |
c.year#c.lnemp1940 |   .4053035   .1503295     2.70   0.007     .1102745    .7003324
                   |
c.year#c.lnmfg1940 |  -.1279643   .0249342    -5.13   0.000    -.1768989   -.0790297
                   |
c.year#c.railroads |   -.000085   .0001626    -0.52   0.601     -.000404    .0002341
                   |
 c.year#c.inst1944 |  -.0560826   .0320036    -1.75   0.080    -.1188912     .006726
                   |
   cap30mile_hydro |   .0982549    .052482     1.87   0.062    -.0047437    .2012534
 cap30mileL2wlight |   .0166672   .0468519     0.36   0.722     -.075282    .1086163
 cap30mileH2wlight |   .1536232   .0281871     5.45   0.000     .0983046    .2089418
             _cons |   1284.568   1851.611     0.69   0.488    -2349.308    4918.444
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |       920         920           0    *|
   state_fips#year |      1025           0        1025     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(ATA8_PC_c2) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap50mileL2wlight cap50mileH2wlight /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      12.15
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6791
                                                  Adj R-squared   =     0.6790
                                                  Within R-sq.    =     0.0246
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8849

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0564528   .0125807     4.49   0.000     .0317802    .0811253
                   |
     c.year#c.lony |   .0367723   .0080242     4.58   0.000     .0210357    .0525089
                   |
             yprcp |   .0001973   .0002736     0.72   0.471    -.0003392    .0007338
              ytav |   .2321408   .1577505     1.47   0.141    -.0772294     .541511
            ydda29 |  -.0049769   .0030853    -1.61   0.107    -.0110275    .0010737
            yddb10 |   .0001297   .0006806     0.19   0.849    -.0012051    .0014645
                   |
c.year#c.lnpop1940 |  -.2166678    .116901    -1.85   0.064    -.4459265    .0125909
                   |
c.year#c.lnemp1940 |    .362884   .1149105     3.16   0.002      .137529     .588239
                   |
c.year#c.lnmfg1940 |  -.1177444   .0182557    -6.45   0.000    -.1535463   -.0819425
                   |
c.year#c.railroads |   -.000098   .0001855    -0.53   0.597    -.0004617    .0002658
                   |
 c.year#c.inst1944 |  -.0319514   .0255843    -1.25   0.212    -.0821257    .0182229
                   |
   cap30mile_hydro |   .0546913   .0652184     0.84   0.402    -.0732109    .1825935
 cap50mileL2wlight |  -.0117838   .0278945    -0.42   0.673    -.0664888    .0429212
 cap50mileH2wlight |    .125457   .0212142     5.91   0.000     .0838531    .1670609
             _cons |   1505.171   1599.233     0.94   0.347    -1631.143    4641.484
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap50mileL2wlight cap50mileH2wlight) nocons /*
> */ ctitle(ATA8_PC_c3) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe imr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap100mileL2wlight cap100mileH2wlight /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,520,156
Absorbing 2 HDFE groups                           F(  14,   2026) =      12.96
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6788
                                                  Adj R-squared   =     0.6788
                                                  Within R-sq.    =     0.0237
Number of clusters (county_fips) =      2,027     Root MSE        =     5.8875

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
               imr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0572695   .0124862     4.59   0.000     .0327824    .0817565
                   |
     c.year#c.lony |    .032121   .0084307     3.81   0.000     .0155874    .0486547
                   |
             yprcp |   .0001905   .0002751     0.69   0.489    -.0003491    .0007301
              ytav |   .2358204   .1579327     1.49   0.136     -.073907    .5455479
            ydda29 |  -.0045206   .0033355    -1.36   0.175    -.0110619    .0020207
            yddb10 |   .0000173   .0006815     0.03   0.980    -.0013192    .0013538
                   |
c.year#c.lnpop1940 |  -.2091821   .1171488    -1.79   0.074    -.4389267    .0205626
                   |
c.year#c.lnemp1940 |    .363464   .1152625     3.15   0.002     .1374186    .5895094
                   |
c.year#c.lnmfg1940 |  -.1241213   .0182509    -6.80   0.000    -.1599137   -.0883289
                   |
c.year#c.railroads |  -1.08e-06   .0001963    -0.01   0.996     -.000386    .0003839
                   |
 c.year#c.inst1944 |  -.0377763   .0261361    -1.45   0.149    -.0890327    .0134801
                   |
   cap30mile_hydro |   .0643572   .0598382     1.08   0.282    -.0529936    .1817081
cap100mileL2wlight |   .0121291   .0151191     0.80   0.423    -.0175215    .0417798
cap100mileH2wlight |   .0796611   .0121425     6.56   0.000      .055848    .1034742
             _cons |    560.767   1662.802     0.34   0.736    -2700.213    3821.747
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap100mileL2wlight cap100mileH2wlight) nocons /*
> */ ctitle(ATA8_PC_c4) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. reghdfe lnimr /*
> */ $Geo $Econ cap30mile_hydro /*
> */ cap30mileL2wlight cap30mileH2wlight /*
> */ [fw=births_rs], absorb(i.county_fips i.state_fips#i.year) cluster(county_fips) 
(MWFE estimator converged in 6 iterations)

HDFE Linear regression                            Number of obs   = 63,468,665
Absorbing 2 HDFE groups                           F(  14,   2026) =      12.64
Statistics robust to heteroskedasticity           Prob > F        =     0.0000
                                                  R-squared       =     0.6405
                                                  Adj R-squared   =     0.6405
                                                  Within R-sq.    =     0.0233
Number of clusters (county_fips) =      2,027     Root MSE        =     0.1926

                              (Std. Err. adjusted for 2,027 clusters in county_fips)
------------------------------------------------------------------------------------
                   |               Robust
             lnimr |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------------+----------------------------------------------------------------
     c.year#c.laty |   .0014404   .0003359     4.29   0.000     .0007817    .0020992
                   |
     c.year#c.lony |   .0010111   .0002102     4.81   0.000     .0005988    .0014233
                   |
             yprcp |   6.40e-06   8.12e-06     0.79   0.431    -9.53e-06    .0000223
              ytav |   .0058896   .0043302     1.36   0.174    -.0026024    .0143817
            ydda29 |  -.0000958   .0000925    -1.04   0.301    -.0002772    .0000856
            yddb10 |  -3.77e-06     .00002    -0.19   0.850     -.000043    .0000355
                   |
c.year#c.lnpop1940 |  -.0051586   .0031179    -1.65   0.098    -.0112734    .0009561
                   |
c.year#c.lnemp1940 |   .0099994   .0030883     3.24   0.001     .0039428     .016056
                   |
c.year#c.lnmfg1940 |  -.0033536    .000512    -6.55   0.000    -.0043577   -.0023495
                   |
c.year#c.railroads |  -4.38e-06   4.78e-06    -0.92   0.359    -.0000138    4.99e-06
                   |
 c.year#c.inst1944 |  -.0011532   .0006742    -1.71   0.087    -.0024754    .0001691
                   |
   cap30mile_hydro |   .0018519   .0018337     1.01   0.313    -.0017443     .005448
 cap30mileL2wlight |    .000311   .0012121     0.26   0.798     -.002066     .002688
 cap30mileH2wlight |   .0055028   .0008959     6.14   0.000     .0037459    .0072598
             _cons |   36.42448   41.21185     0.88   0.377    -44.39754    117.2465
------------------------------------------------------------------------------------

Absorbed degrees of freedom:
-----------------------------------------------------------+
       Absorbed FE | Categories  - Redundant  = Num. Coefs |
-------------------+---------------------------------------|
       county_fips |      2027        2027           0    *|
   state_fips#year |      1075           0        1075     |
-----------------------------------------------------------+
* = FE nested within cluster; treated as redundant for DoF computation

. outreg2 /*
> */ using logfiles/Canary_output, /*
> */ keep(cap30mileL2wlight cap30mileH2wlight) nocons /*
> */ ctitle(ATA8_PC_c5) se bdec(3) sdec(3) rdec(3) excel append
logfiles/Canary_output.xml
dir : seeout

. 
. 
. 
. log close
      name:  <unnamed>
       log:  /Users/edson/Dropbox/Electricity_CLS/Canary_Codes_Data/logfiles/Canary_logfile.log
  log type:  text
 closed on:  30 Jun 2022, 15:39:38
-------------------------------------------------------------------------------------------------------------------------
